37 Random Forest Jobs

A strong level of proficiency in python programming. Practical knowledge and working experience on Statistics and Operation Research methods. Practical knowledge and working experience in tools and frameworks like Flask, PySpark,Pytorch,tensorflow, keras, Databricks, OpenCV, Pillow/PIL, streamlit, d3js, dashplotly, neo4j. Hands on experience in Analytics/AI-ML AWS services like Sagemaker, Canvas, Bedrock. Good understanding of how to apply predictive and machine learning techniques like regression models, XGBoost, random forest, GBM, Neural Nets, SVM etc. Proficient with NLP techniques like RNN, LSTM and Attention based models and effectively handle readily available stanford, IBM, Azure, Open AI NLP models. Good understanding of SQL from a perspective of how to write efficient queries for pulling the data from database. Hands on experience on any version control tool (github, bitbucket). Experience of deploying ML models into production environment experience (MLOps) in any one of the cloud platforms like Azure and AWS. Understanding business needs / mapping it to the business processes. Hands on experience in agile project delivery. Good in conceptualizing and visualizing end to end business needs both at high level as well as detailed. Good in articulating the business needs. Good analytical and problem-solving skills. Good communication, listening and probing skills. Strong inter-personnel skills. Should collaborate with other team members and work as team. Job Description: Comprehend business issues and propose valuable business solutions. Design Factual or AI/profound learning models to address business issues. Design Statistical Models/ ML/DL models and deploy them for production. Formulate what information is accessible from where and how to augment it. Develop innovative graphs for data comprehension using d3js, dashplotly and neo4j. Preferred Certification: (Good to have) AWS Specialty Certification in Data Analytics, Machine Learning.

Requirement : Bachelor's Degree in Computer Science, Operations Research, Statistics, or related field. Knowledge of R, or Python Knowledge of building regression and classification models Familiarity with any or all of, Regularization methods: Lasso, Ridge Ensemble methods: Random Forest, Boosting Time Series analysis: Auto-regression, moving average, etc. Graphs modeling Support Vector Machines Decision trees Preferred : Master's or higher degrees. Industry experience in the field of Data Science. Participation in competitions like Kaggle, Netflix Data Challenge. Open source contributions in areas of Data Science (Machine Learning, Deep Learning, Statistical Learning). Worked on Scala and/or Spark. Understanding of generative AI concepts, such as transformers, diffusion models, and LLMs

In the IBM Chief Information Office,you wi be part of a dynamic team driving the future of AI and data science in arge-scae enterprise transformations. We offer a coaborative environment where your technica expertise wi be vaued, and your professiona deveopment wi be supported. Join us to work on chaenging projects, everage the atest technoogies, and make a tangibe impact on eading organisations. As a Data Scientist within IBM's Chief Information Office, you wi support AI-driven projects across the enterprise. You wi appy your technica skis in AI, machine earning, and data anaytics to assist in impementing data-driven soutions that aign with business goas. This roe invoves working with team members to transate data insights into actionabe recommendations. Key Responsibiities: Technica Execution and Leadership: Deveop and depoy AI modes and data anaytics soutions. Support the impementation and optimisation of AI-driven strategies per business stakehoder requirements. Hep refine data-driven methodoogies for transformation projects. Data Science and AI: Design and impement machine earning soutions and statistica modes, from probem formuation through depoyment, to anayse compex datasets and generate actionabe insights. Learn and utiise coud patforms to ensure the scaabiity of AI soutions. Leverage reusabe assets and appy IBM standards for data science and deveopment. Project Support: Lead and contribute to various stages of AI and data science projects, from data exporation to mode deveopment. Monitor project timeines and hep resove technica chaenges. Design and impement measurement frameworks to benchmark AI soutions, quantifying business impact through KPIs. Coaboration: Ensure aignment to stakehoders strategic direction and tactica needs. Work with data engineers, software deveopers, and other team members to integrate AI soutions into existing systems. Contribute technica expertise to cross-functiona teams. Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Bacheors or Masters in Computer Science, Data Science, Statistics, or a reated fied is required; an advanced degree is strongy preferred Experience: 5+ yearsof experience in data science, AI, or anaytics with a focus on impementing data-driven soutions Experience with data ceaning, data anaysis, A/B testing, and data visuaization Experience with AI technoogies through coursework or projects Technica Skis: Proficiency in SQL and Python for performing data anaysis and deveoping machine earning modes Knowedge of common machine earning agorithms and frameworksinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neura networks, and deep earning frameworks such as TensorFow and PyTorch Experience with coud-based patforms and data processing frameworks Understanding of arge anguage modes (LLMs) Famiiarity with IBMs watsonx product suite Famiiarity with object-oriented programming Anaytica Skis: Strong probem-soving abiities and eagerness to earn

Job Title: Data Scientist Location: Bangalore, India Experience: 3+ Years Role & Responsibilities: We are looking for a highly motivated Data Scientist to join our analytics team in Bangalore. This role is ideal for individuals who possess strong machine learning and data engineering skills and are eager to solve complex problems in the financial technology space. You will work on developing predictive models, building scalable data solutions, and contributing to key decision-making processes. Design, build, and validate machine learning models including Logistic Regression, Random Forests, GBM, and Survival Models. Perform rigorous model evaluation using techniques such as K-Fold Cross Validation, Out-of-Time (OOT) validation, and X-Tab analysis. Utilize Python (via PyCharm/Jupiter), scikit-learn, PyTorch or TensorFlow for end-to-end model development. Analyse large datasets using SQL and Excel to derive actionable insights. Develop and deploy APIs to serve machine learning models in production environments. Apply statistical techniques such as mean/variance analysis, probability distributions, and simulations to drive model accuracy and relevance. (Optional) Work with lending-specific metrics such as vintage curves, roll forward tracking, and bounce rates to enhance financial models. Strong ML skills: Logistic, Random Forest, GBM, survival model, K fold test, OOT, X-Tab etc. Experience using scikit-learn, pytorch or tensor flow. Experience: 3+ Years Python and usage of PyCharm/ Jupiter, SQL, Excel. Well versed in API development - Strong mathematical ability. mean, variance, probability distributions, simulation etc. Understanding of lending metrics such as vintage curve, roll forward, bounces etc. (Good to have not mandatory) Engineering background preferred IIT/NIT plus not must. Prior experience in Lending Fintech preferred.

We're Hiring: Data Scientist Databricks & ML Deployment Expert Location: Mumbai/Pune Experience: 38 Years Apply Now! Are you passionate about deploying real-world machine learning solutions? We're looking for a versatile Data Scientist with deep expertise in Databricks, PySpark , and end-to-end ML deployment to drive impactful projects in the Retail and Automotive domains. What Youll Do Develop scalable ML models (Regression, Classification, Clustering) Deliver advanced use cases like CLV modeling , Predictive Maintenance , and Time Series Forecasting Design and automate ML workflows on Databricks using PySpark Build and deploy APIs to serve ML models (Flask, FastAPI, Django) Own model deployment and monitoring in production environments Work closely with Data Engineering and DevOps teams for CI/CD integration Optimize pipelines and model performance (code & infrastructure level) Must-Have Skills Strong hands-on with Databricks and PySpark Proven track record in ML model development & deployment (min. 2 production deployments) Solid grasp of Regression, Classification, Clustering & Time Series Proficiency in SQL , workflow automation, and ELT/ETL processes API development (Flask, FastAPI, Django) CI/CD, deployment automation, and ML pipeline optimization Familiarity with Medallion Architecture Domain Expertise Retail : CLV, Pricing, Demand Forecasting Automotive : Predictive Maintenance, Time Series Nice to Have MLflow, Docker, Kubernetes Cloud: Azure, AWS, or GCP If you're excited to build production-ready ML systems that create real business impact, we want to hear from you! Apply Now to chaity.mukherjee@celebaltech.com.

Position Overview As the newest addition to our existing Data Science team, youll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. Youll help drive product development using our vast user data sets to enhance our current products and to help us find inferences and relationships in this data to build new productsMore towards the role required Company Overview BOLD is an established and fast-growing product company that transforms work lives. Since 2005, weve helped more than 10,000,000 folks from all over America(and beyond!) reach higher and do better. A career at BOLD promises great challenges, opportunities, culture and the environment. With our headquarters in Puerto Rico and offices in San Francisco and India, were a global organization on a path to change the career industry. Key Responsibilities Demonstrate ability to work on data science projects involving NLP, large language models, predictive modelling, statistical analysis, vector space modelling, machine learning etc. Leverage our rich data sets of user data to perform research, develop models and create data products with our Development & Product teams Develop novel and scalable data systems in cooperation with our system architects that leverage datasets using machine learning techniques to enhance the user experience Collaborates effectively with cross functional teams to deliver end-to-end products & features. Demonstrates ability to multi-task and re-prioritize responsibilities based on changing requirements. Estimates efforts, identify risks, devises and meets project schedules. Runs review meetings effectively and drive the closure of all open issues on time Mentors/coaches data scientists to facilitate their development and provide technical leadership to them. Rises above detail to see broader issues and implications for whole product/team Required Skills Knowledge and experience using statistical and machine learning algorithms including regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods Expert knowledge in Python. Experience in using large language models. Experience in feature selection, building and optimizing classifiers. Experience working with backend technologies such asFlask/Gunicorn etc. Experience on working with open source library such Spacy, NLTK, Gensim etc Experience on working with deep-learning library such as Tensor flow, Pytorch etc. Experience with software stack components including common programming languages, back-end technologies, database modelling, continuous integration, services oriented architecture, software testability etc. Be a keen learner and enthusiastic about developing software

Role Overview: As a Data Scientist within IBM's Chief Analytics Office, you will support AI-driven projects across the enterprise. You will apply your technical skills in AI, machine learning, and data analytics to assist in implementing data-driven solutions that align with business goals. This role involves working with team members to translate data insights into actionable recommendations. Key Responsibilities: Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Support the implementation and optimization of AI-driven strategies per business stakeholder requirements. Help refine data-driven methodologies for transformation projects. Data Science and AI: Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights. Learn and utilize cloud platforms to ensure the scalability of AI solutions. Leverage reusable assets and apply IBM standards for data science and development. Project Support: Lead and contribute to various stages of AI and data science projects, from data exploration to model development. Monitor project timelines and help resolve technical challenges. Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. Collaboration: Ensure alignment to stakeholders’ strategic direction and tactical needs. Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Contribute technical expertise to cross-functional teams. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Education: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related field is required; an advanced degree strongly preferred Experience: 5+ yearsof experience in data science, AI, or analytics with a focus on implementing data-driven solutions Experience with data cleaning, data analysis, A/B testing, and data visualization Experience with AI technologies through coursework or projects Technical Skills: Proficiency in SQL and Python for performing data analysis and developing machine learning models Knowledge of common machine learning algorithms and frameworkslinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience with cloud-based platforms and data processing frameworks Understanding of large language models (LLMs) Familiarity with IBM’s watsonx product suite Familiarity with object-oriented programming Analytical Skills: Strong problem-solving abilities and eagerness to learn Ability to work with datasets and derive insights Other : Good communication skills, with the ability to explain technical concepts clearly Enthusiasm for learning and applying new technologies Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment Successful completion of Coding Assessment Preferred technical and professional experience Advanced degree strongly preferred

Location:Bangalore/Gurgaon/Hyderabad/Mumbai Must have skills: Must have skills:Data Scientist / Transformation Leader & at least 5 years in Telecom Analytics Good to have skills:GEN AI, Agentic AI, Job Summary : About Global Network Data & AI:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition About Comms & Media practice: Comms & Media (C&M) is one of the Industry Practices within Accentures S&C Global Network team. It focuses in serving clients across specific Industries Communications, Media & Entertainment. Communications Focuses primarily on industries related with telecommunications and information & communication technology (ICT). This team serves most of the worlds leading wireline, wireless, cable and satellite communications and service providers Media & Entertainment Focuses on industries like broadcast, entertainment, print and publishing Globally, Accenture Comms & Media practice works to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Roles & Responsibilities: A Telco domain experienced and data science consultant is responsible to help the clients with designing & delivering AI solutions. He/she should be strong in Telco domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Professional & Technical Skills: Overall 10+ years of experience in Data Science & at least 5 years in Telecom Analytics Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software (one or more) Python, R, PySpark, SQL, BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Qualification Experience: Overall 10+ years of experience in Data Science & at least 5 years in Telecom Educational Qualification: Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school

Job Title - S&C Global Network - AI - CMT - Consultant Data Science Management Level: 9-Team Lead/Consultant Location: Hyderabad, HDC2A Must-have skills: CMT Analytics Good to have skills: Ability to leverage design thinking, business process optimization, and stakeholder management skills. Job Summary : This role involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. Roles & Responsibilities: Provide strategic advisory services, conduct market research, and develop data-driven recommendations to enhance business performance. Responsibilities/Authorities A Telco domain experienced and data science consultant is responsible to help the clients with designing & delivering AI solutions. He/she should be strong in Telco domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Should be able to travel or relocate to Japan as per business requirement. Professional & Technical Skills: - Relevant experience in the required domain. - Strong analytical, problem-solving, and communication skills. - Ability to work in a fast-paced, dynamic environment. Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software (one or more) Python, R, PySpark, SQL, BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Additional Information: - Opportunity to work on innovative projects. - Career growth and leadership exposure. About Our Company | Accenture Qualification Experience: 8-10Years Educational Qualification: Any Degree

Title : Senior Manager -Data Science, Machine Learning and GenAI Technical Leader Job Area: Information Technology Group, Information Technology Group > IT Management General Summary: Experience in engaging with business and technical stakeholders, understanding complex problem statements, and proposing value-driven Data Science & ML solutionsFunctional & technical leadership in developing data science roadmap and guiding the team with end-to-end delivery (design, development, maintenance, and optimization) of advanced analytical solutions with focus on process standardization and best practicesProactive in reaching out to wide variety of stakeholders for increasing the awareness of Data Science, ML and GenAI capabilities and identifying business value driven opportunitiesAnalyze the market and industry trends in the technology and proactively look for opportunities in bringing the best solutions 'Strong analytical skills with the ability to gather information from several sources and identify fundamental patterns/trends in dataConduct research, design statistical studies and develop solutionsDevelop Story Telling dashboards on analytics to assist business in decision makingImplement deep learning models for structured and unstructured data setsPerform Time Series Analysis and Forecast (ARIMA, Exponential Smoothing, VAR etc.)Implementation experience with identifying, prototyping, developing and delivering GenAI solutions using Industry standard RAG models and frameworksAbility to develop capabilities in Text Analytics ranging from Basic to Advanced (Topic Modelling, NLP)Experience with AWS suite of Data Science and ML toolsDevelops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, Catboost etc.) 'Experience with other cloud platforms (GCP and Azure)Understanding of Data Platforms and Data EngineeringExposure to ChatBot solutions and Automation technologies Minimum Qualifications: 7+ years of IT-related work experience with a Bachelor's degree. OR 9+ years of IT-related work experience without a Bachelors degree. 4+ years in a leadership role in projects/programs.

hands on SQL/ SAS programming experience & handling complex/large data Must have experience inTableau/Power BI Experience in campaign performance measurement, customer targeting framework Proven ability to design and lead strategic projects Required Candidate profile Must - SAS , SQL, Python Good in Statistical model , Predictive model, Logistic regression, Linear regression BFSI Mandatory - Credit risk, Credit Card, Retail Banking

Role Overview: As a Data Scientist within IBM's Chief Analytics Office, you will support AI-driven projects across the enterprise. You will apply your technical skills in AI, machine learning, and data analytics to assist in implementing data-driven solutions that align with business goals. This role involves working with team members to translate data insights into actionable recommendations. Key Responsibilities: Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Support the implementation and optimization of AI-driven strategies per business stakeholder requirements. Help refine data-driven methodologies for transformation projects. Data Science and AI: Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights. Learn and utilize cloud platforms to ensure the scalability of AI solutions. Leverage reusable assets and apply IBM standards for data science and development. Project Support: Lead and contribute to various stages of AI and data science projects, from data exploration to model development. Monitor project timelines and help resolve technical challenges. Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. Collaboration: Ensure alignment to stakeholders’ strategic direction and tactical needs. Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Contribute technical expertise to cross-functional teams. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Education: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related field is required; an advanced degree strongly preferred Experience: 2-4 yearsof experience in data science, AI, or analytics with a focus on implementing data-driven solutions Experience with data cleaning, data analysis, A/B testing, and data visualization Experience with AI technologies through coursework or projects Technical Skills: Proficiency in SQL and Python for performing data analysis and developing machine learning models Knowledge of common machine learning algorithms and frameworkslinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience with cloud-based platforms and data processing frameworks Understanding of large language models (LLMs) Familiarity with IBM’s watsonx product suite Familiarity with object-oriented programming Analytical Skills: Strong problem-solving abilities and eagerness to learn Ability to work with datasets and derive insights Other : Good communication skills, with the ability to explain technical concepts clearly Enthusiasm for learning and applying new technologies Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment Successful completion of Coding Assessment Preferred technical and professional experience Advanced degree strongly preferred

We are seeking a talented and motivated Data Scientist with 1-3 years of experience to join our Data Science team. If you have a strong passion for data science, expertise in machine learning, and experience working with large-scale datasets, we want to hear from you. As a Data Scientist at RevX, you will play a crucial role in developing and implementing machine learning models to drive business impact. You will work closely with teams across data science, engineering, product, and campaign management to build predictive models, optimize algorithms, and deliver actionable insights. Your work will directly influence business strategy, product development, and campaign optimization. Major Responsibilities: Develop and implement machine learning models, particularly neural networks, decision trees, random forests, and XGBoost, to solve complex business problems. Work on deep learning models and other advanced techniques to enhance predictive accuracy and model performance. Analyze and interpret large, complex datasets using Python, SQL, and big data technologies to derive meaningful insights. Collaborate with cross-functional teams to design, build, and deploy end-to-end data science solutions, including data pipelines and model deployment frameworks. Utilize advanced statistical techniques and machine learning methodologies to optimize business strategies and outcomes. Evaluate and improve model performance, calibration, and deployment strategies for real-time applications. Perform clustering, segmentation, and other unsupervised learning techniques to discover patterns in large datasets. Conduct A/B testing and other experimental designs to validate model performance and business strategies. Create and maintain data visualizations and dashboards using tools such as matplotlib, seaborn, Grafana, and Looker to communicate findings. Provide technical expertise in handling big data, data warehousing, and cloud-based platforms like Google Cloud Platform (GCP). Required Experience/Skills: Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. 1-3 years of experience in data science or machine learning roles. Strong proficiency in Python for machine learning, data analysis, and deep learning applications. Experience in developing, deploying, and monitoring machine learning models, particularly neural networks, and other advanced algorithms. Expertise in handling big data technologies, with experience in tools such as BigQuery and cloud platforms (GCP preferred). Advanced SQL skills for data querying and manipulation from large datasets. Experience in data visualization tools like matplotlib, seaborn, Grafana, and Looker. Strong understanding of A/B testing, statistical tests, experimental design, and methodologies. Experience in clustering, segmentation, and other unsupervised learning techniques. Strong problem-solving skills and the ability to work with complex datasets and machine learning pipelines. Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Preferred Skills: Experience with deep learning frameworks such as TensorFlow or PyTorch. Familiarity with data warehousing concepts and big data tools. Knowledge of MLOps practices, including model deployment, monitoring, and management. Experience with business intelligence tools and creating data-driven dashboards. Understanding of reinforcement learning, natural language processing (NLP), or other advanced AI techniques. Education: Bachelor of Engineering or similar degree from any reputed University.

Research and Problem-Solving: Identify and frame business problems, conduct exploratory data analysis, and propose innovative data science solutions tailored to business needs. Leadership & Communication: Serve as a technical referent for the research team, driving high-impact, high-visibility initiatives. Effectively communicate complex scientific concepts to senior stakeholders, ensuring insights are actionable for both technical and non-technical audiences. Mentor and develop scientists within the team, fostering growth and technical excellence. Algorithm Development: Design, optimize, and implement advanced machine learning algorithms, including neural networks, ensemble models (XGBoost, random forests), and clustering techniques. End-to-End Project Ownership: Lead the development, deployment, and monitoring of machine learning models and data pipelines for large-scale applications. Model Optimization and Scalability: Focus on optimizing algorithms for performance and scalability, ensuring robust, well-calibrated models suitable for real-time environments. A/B Testing and Validation: Design and execute experiments, including A/B testing, to validate model effectiveness and business impat. Big Data Handling: Leverage tools like BigQuery, advanced SQL, and cloud platforms (e.g., GCP) to process and analyze large datasets. Collaboration and Mentorship: Work closely with engineering, product, and campaign management teams, while mentoring junior data scientists in best practices and advanced techniques. Data Visualization: Create impactful visualizations using tools like matplotlib, seaborn, Looker, and Grafana to communicate insights effectively to stakeholders. Required Experience/Skills 5–8 years of hands-on experience in data science or machine learning roles. 2+ years leading data science projects in AdTech Strong hands-on skills in Advanced Statistics, Machine Learning, and Deep Learning. Demonstrated ability to implement and optimize neural networks and other advanced ML models. Proficiency in Python for developing machine learning models, with a strong grasp of TensorFlow or PyTorch. Expertise handling large datasets using advanced SQL and big data tools like BigQuery In-depth knowledge of MLOps pipelines, from data preprocessing to deployment and monitoring. Strong background in A/B testing, statistical analysis, and experimental design. Proven capability in clustering, segmentation, and unsupervised learning methods. Strong problem-solving and analytical skills with a focus on delivering business value. Education: A Master’s in Data Science, Computer Science, Mathematics, Statistics, or a related field is preferred. A Bachelor's degree with exceptional experience will also be considered.

Career Area: Technology, Digital and Data : Your Work Shapes the World at Caterpillar Inc. When you join Caterpillar, you're joining a global team who cares not just about the work we do - but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here - we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Your Impact Shapes the World at Caterpillar Inc When you join Caterpillar, you're joining a global team who cares not just about the work we do - but also about each other. We are the makers, problem solvers and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here - we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Job Summary Caterpillar is seeking a skilled Senior Data Scientist to join our team to act as a champion for our Digital Finance-Disruptive Technology Team within the Global Finance Services Division . The incumbent will leverage internal data and advanced analytics to solve business problems. The preference for this role is to be based out of Whitefield Office, Bangalore, India What you will do As a Senior Data Scientist, you will work in a team environment with a group of data scientists and software developers to support the development, integration, and enhancement of Caterpillar's analytics, AI, and Generative AI projects and products. Gain an understanding of Caterpillar s business and accounting practices, systems, and procedures. Developing ML/AI/GenAI models and solutions. Performing data gathering, data mining, and data processing on large volumes of data; creating appropriate data models. Demonstrating a breadth of knowledge in the application of ML/AI/GenAI and statistical methods and/or digital methods to solve business problems. Conducting research on data model optimization and algorithms to improve the effectiveness and accuracy of data analyses. Participating on 1-3 primary projects concurrently. Having a strong focus on continual learning in the Analytics field. Reporting and presenting team results. The Data Scientist will develop good networks within the technical community to enable them to collaborate on technical solutions, obtain resources and cooperation needed, and remove roadblocks so that they can ensure the success of their projects. What you will have Typically, a Bachelor's, Master s, or Ph.D. degree, preferably in statistics, economics, mathematics, or a similar field with quantitative coursework. 5+ Years of Professional Experience with the ability to deliver data science products with almost no technical guidance from others. The ability to provide technical guidance to less experience data science team members. Experience with data analysis and statistical methods such as regression, hypothesis testing, ANOVA, statistical process control, etc. Practical applications of machine learning techniques such as clustering, logistic regression, CART, random forests, SVM, or neural networks. Technical and problem-solving skills with evidence of continuous learning in the analytics field. Breadth and depth of knowledge in the application of statistical and/or digital methods to solve business problems. Experience with projects connecting data from various business domains and providing forecasts and insights to run the business profitably. Working knowledge of cloud technologies (AWS, Azure, Google Cloud, etc.). Working knowledge of version control/repositories such as GitHub. Experience operating in an Agile environment. Initiative to research and apply new methods and digital technologies to exceed customer expectations. Must demonstrate strong initiative, interpersonal skills, and the ability to communicate effectively. Must be comfortable working in MS Office, and industry standard statistics, analytics, and data visualization packages. Experience mechanizing manual data collection processes using Snowflake to enhance indicative data to generate quicker and more granular insights. Tables/Process could be leveraged by the Forecasting and Financial Analysis Reporting groups. Experience with writing fast and memory-efficient code as well as with various types of parallel processingthreading, multi-core/forking, multiple session, and cluster computing. Skills desired: Analytical Thinking Extensive knowledge of techniques and tools for effective analysis; ability to determine the root cause of problems and create alternative solutions that resolve these issues. GenAI / AI / Machine Learning Extensive experience and knowledge of the principles, technologies, and algorithms of GenAI, AI, and machine learning; ability to develop, implement, and deliver related systems, products, and services. Statistics Extensive knowledge of statistical tools, processes, and practices to describe results on measurable scales; ability to use statistical tools and processes to assist in making business decisions. Programming Languages Extensive experience in applying Python (NumPy, SciPy, Pandas, etc.) to solve business challenges; ability to use tools, techniques, and platforms to write and modify programming languages. Information Processing Extensive experience in processing large quantities of detailed information with high levels of accuracy. Databases Extensive knowledge in writing, debugging, and implementing complex queries involving multiple tables or databases. Presentation Skills Strong presentation and communication skills. What you will get: Work Life Harmony Earned and medical leave. Flexible work arrangements Relocation assistance Holistic Development Personal and professional development through Caterpillar s employee resource groups across the globe Career developments opportunities with global prospects Health and Wellness Medical coverage -Medical, life and personal accident coverage Employee mental wellness assistance program Financial Wellness Employee investment plan Pay for performance -Annual incentive Bonus plan. Additional Information: Caterpillar is not currently hiring individuals for this position who now or in the future require sponsorship for employment visa status; however, as a global company, Caterpillar offers many job opportunities outside of the U.S. which can be found through our employment website at www.caterpillar.com/careers Posting Dates: January 16, 2025 - January 29, 2025 Caterpillar is an Equal Opportunity Employer (EEO). Not ready to applyJoin our Talent Community .

Data Scientist (6-8 Years Experience) Company Overview Accenture is a global professional services company with leading capabilities in digital, cloud, and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology, and Operations services"”all powered by the world's largest network of Advanced Technology and Intelligent Operations centers. Our 700,000+ people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners, and communities. At Accenture, we offer a dynamic and challenging environment for analytical and creative minds. We value a diverse workforce committed to achieving client goals and delivering results. Were built on a foundation of exceptional talent and are on the lookout for driven, energetic professionals to enhance our team. Key Responsibilities Data Handling Data Collection:Participate in calls with stakeholders (internal and external, based in the US) to gather data from various sources (email, Dropbox, Egnyte, databases). Data Audit:Lead assessment of data quality, identify gaps, and create summaries as per database requirements. Data Scrubbing:Assist with creating data cleansing rules and incorporate data clarifications provided by data source owners. Data Profiling:Assist with creating multi-dimensional data views, data analysis reports, and extracts. Data Classification Spend Classification:Analyze procurement spend using several techniques to comprehensively classify into a custom taxonomy in Accenture's spend analytics tool. Enhancements:Diligently incorporate feedback and make recommendations for process improvement. Report Generation:Create specific and opportunity spend-assessment reports/templates. Periodic Refreshes:Lead discussions with US-based stakeholders for data gathering, data quality checks, control total validation, and spend classification. Advanced Analytics and AI/ML Develop custom data models and algorithms to apply to data sets. Use machine learning tools and statistical techniques to produce solutions to problems. Implement clustering and auto classification using predictive and supervised learning techniques. Design and implement complex data models from scratch. Develop and optimize ETL processes to ensure efficient data handling and processing. Create intuitive and effective front-end interfaces from scratch. Apply AI/ML techniques to optimize supply chain management, including demand forecasting, inventory optimization, and supplier performance analysis. Utilize advanced machine learning algorithms and statistics:regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Develop and implement AI/ML models for predictive analytics and automated decision-making in supply chain operations. Industry Research Secondary Research:Conduct market research to create company and industry primers using online secondary data or information sources. Technical Requirements Python:Hands-on experience with threading limitations and multi-process architecture. MySQL:Ability to integrate multiple data sources using MySQL. Strong coding knowledge and experience with several languages (e.g., R, SQL, JavaScript, Java, CSS, C++). Familiarity with statistical and data mining techniques (e.g., GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis). Experience with advanced machine learning algorithms and statistics:regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Collaboration and Communication Coordinate with different functional teams to implement models and monitor outcomes. Develop processes and tools to monitor and analyze model performance and data accuracy. Excellent spoken and written English communication skills, with the ability to participate in global team calls. Other Important Details Work Location:Gurugram, India Expected Start Dates:July 2024 Qualifications Who Should Apply? Work Experience:6-8 years of relevant experience in data modeling, ETL automation, AI/ML, and front-end design. Academic Qualifications:Bachelor’s or Master’s degree in Engineering, Mathematics, Computer Science, or a related field. Job Requirements: - Extensive experience in handling and classifying spend data using AI/ML Techniques. - Strong leadership and team management skills. - Proficiency in MS Excel and MS PowerPoint. - High attention to detail, accuracy, and innovative problem-solving skills. - Preferred experience in supply chain management, with a focus on applying AI/ML techniques to optimize operations.

Role Overview: As a Data Scientist within IBM's Chief Analytics Office, you will support AI-driven projects across the enterprise. You will apply your technical skills in AI, machine learning, and data analytics to assist in implementing data-driven solutions that align with business goals. This role involves working with team members to translate data insights into actionable recommendations. Key Responsibilities: Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Support the implementation and optimization of AI-driven strategies per business stakeholder requirements. Help refine data-driven methodologies for transformation projects. Data Science and AI: Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights. Learn and utilize cloud platforms to ensure the scalability of AI solutions. Leverage reusable assets and apply IBM standards for data science and development. Project Support: Lead and contribute to various stages of AI and data science projects, from data exploration to model development. Monitor project timelines and help resolve technical challenges. Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. Collaboration: Ensure alignment to stakeholders’ strategic direction and tactical needs. Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Contribute technical expertise to cross-functional teams. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Education: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related field is required; an advanced degree strongly preferred Experience: 2-4 yearsof experience in data science, AI, or analytics with a focus on implementing data-driven solutions Experience with data cleaning, data analysis, A/B testing, and data visualization Experience with AI technologies through coursework or projects Technical Skills: Proficiency in SQL and Python for performing data analysis and developing machine learning models Knowledge of common machine learning algorithms and frameworkslinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience with cloud-based platforms and data processing frameworks Understanding of large language models (LLMs) Familiarity with IBM’s watsonx product suite Familiarity with object-oriented programming Analytical Skills: Strong problem-solving abilities and eagerness to learn Ability to work with datasets and derive insights Other Requirements: Good communication skills, with the ability to explain technical concepts clearly Enthusiasm for learning and applying new technologies Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment Successful completion of Coding Assessment Preferred technical and professional experience Advanced degree strongly preferred

Role Overview: As a Data Scientist within IBM's Chief Analytics Office, you will support AI-driven projects across the enterprise. You will apply your technical skills in AI, machine learning, and data analytics to assist in implementing data-driven solutions that align with business goals. This role involves working with team members to translate data insights into actionable recommendations. Key Responsibilities: Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Support the implementation and optimization of AI-driven strategies per business stakeholder requirements. Help refine data-driven methodologies for transformation projects. Data Science and AI: Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights. Learn and utilize cloud platforms to ensure the scalability of AI solutions. Leverage reusable assets and apply IBM standards for data science and development. Project Support: Lead and contribute to various stages of AI and data science projects, from data exploration to model development. Monitor project timelines and help resolve technical challenges. Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. Collaboration: Ensure alignment to stakeholders’ strategic direction and tactical needs. Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Contribute technical expertise to cross-functional teams. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Education: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related field is required; an advanced degree is strongly preferred Experience: 5+ yearsof experience in data science, AI, or analytics with a focus on implementing data-driven solutions Experience with data cleaning, data analysis, A/B testing, and data visualization Experience with AI technologies through coursework or projects Technical Skills: Proficiency in SQL and Python for performing data analysis and developing machine learning models Knowledge of common machine learning algorithms and frameworkslinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience with cloud-based platforms and data processing frameworks Understanding of large language models (LLMs) Familiarity with IBM’s watsonx product suite Familiarity with object-oriented programming Analytical Skills: Strong problem-solving abilities and eagerness to learn Ability to work with datasets and derive insights Other Requirements: Good communication skills, with the ability to explain technical concepts clearly Enthusiasm for learning and applying new technologies Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment Successful completion of Coding Assessment Preferred technical and professional experience Advanced degree strongly preferred

Job Description: We are seeking an experienced Data Scientist with expertise in advanced machine learning techniques to join our dynamic team. The ideal candidate will have hands-on experience developing and deploying models using ensemble methods and other cutting-edge ML algorithms, mostly in the US banking domain. Key Responsibilities: Develop and help deploy advanced machine learning models, including ensemble techniques, for customer lifecycle use cases (e.g., prescreen, acquisition, account management, collections, and fraud). Collaborate with cross-functional teams to define, develop, and improve predictive models that drive business decisions. Work with large datasets, utilizing tools like Python and SQL , to extract, clean, and transform data for modeling purposes. Ensure model robustness, interpretability, and scalability within banking environments. Strong problem-solving skills with the ability to handle complex datasets and turn them into actionable insights.

Data Scientist with experience in projects related to Churn- Machine learning-random Forest-XGBoost-Logistics Regression. candidate must be an immediate Joiner or 30 Days NP

Role & responsibilities Requires 5-8 years of proven experience in banking/payments/other domains Strong experience in developing Machine Learning models, Python & SQL Experience working with pre-trained models, awareness of state-of-art in embeddings and applicability for use cases Detailed oriented with a proactive mindset towards problem-solving Excellent communication and presentation skills with the ability to convey complex information clearly and concisely Demonstrated ability to engage with client stake holders

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together Primary Responsibilities Applying knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement Data mining using state-of-the-art methods Enhancing data collection procedures to include information that is relevant for building analytic systems Processing, cleansing, and verifying the integrity of data used for analysis Doing ad-hoc analysis and presenting results in a clear manner Working with analytics and statistical software such as SQL, R, Python, Hadoop and others to perform analysis and interpret data Work with stakeholders to identify opportunities for leveraging company data to drive business solutions. Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies Assess the effectiveness and accuracy of new data sources and data gathering techniques Develop custom data models and algorithms to apply to data sets Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes Develop company A/B testing framework and test model quality Coordinate with different functional teams to implement models and monitor outcomes Develop processes and tools to monitor and analyze model performance and data accuracy Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Graduate degree or equivalent experience Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets Experience working with and creating data architectures Experience querying databases and using statistical computer languagesR, Python, SLQ, etc. Experience using web servicesRedshift, S3, Spark, DigitalOcean, etc. Experience creating and using advanced machine learning algorithms and statisticsregression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Experience with distributed data/computing toolsMap/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc. Experience visualizing/presenting data for stakeholders usingPeriscope, Business Objects, D3, ggplot, etc. Solid problem solving skills with an emphasis on product development Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications Proven excellent written and verbal communication skills for coordinating across teams A drive to learn and master new technologies and techniques Coding knowledge and experience with several languagesC, C++, Java, JavaScript, etc. Knowledge and experience in statistical and data mining techniquesGLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, k-NN, Naive Bayes, SVM, etc. At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

Strong proficiency in Python and/or R for data analysis and modeling. Advanced SQL skills for data querying and transformation. Hands-on experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Solid understanding of statistics, hypothesis testing, regression analysis, and data mining. Familiarity with cloud platforms (AWS, Azure, or GCP) and big data tools (Spark, Hadoop) is a plus. Excellent problem-solving skills and attention to detail.

Job Title - Data Scientist and Analytics Level 7:Manager Ind & Func AI Decision Science Manager S&C Management Level:07 - Manager Location Bangalore/Gurgaon/Hyderabad/Mumbai Must have skills: Technical (Python, SQL, ML and AI), Functional (Data Scientist and B2B Analytics preferably in Telco and S&P industries) Good to have skillsGEN AI, Agentic AI, cloud (AWS/Azure, GCP) Job Summary : About Global Network Data & AI:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition About Comms & Media practice The Accenture Center for Data and Insights (CDI) team helps businesses integrate data and AI into their operations to drive innovation and business growth by designing and implementing data strategies, generating actionable insights from data, and enabling clients to make informed decisions. In CDI, we leverage AI (predictive + generative), analytics, and automation to build innovative and practical solutions, tools and capabilities. The team is also working on building and socializing a Marketplace to democratize data and AI solutions within Accenture and for clients. Globally, CDI practice works across industry to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Roles & Responsibilities: Experienced in Analytics in B2B domain. Responsible to help the clients with designing & delivering AI/ML solutions. He/she should be strong in Telco and S&P domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Data manipulation and aggregation using Python. Propensity modeling using various ML algorithms. Text mining using NLP/AI techniques Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients' business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Professional & Technical Skills: Overall 10+ years of experience in Data Science B.Tech Engineering from Tier 1 school or Msc in Statistics/Data Science from a Tier 1/Tier 2 Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software Python (must), R, PySpark, SQL (must), BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Qualifications Experience: B.Tech Engineering from Tier 1 school or Msc in Statistics/Data Science from a Tier 1/Tier 2 Educational Qualification: B.tech or MSC in Statistics and Data Science

Required Skills & Qualifications: 3-5 years of hands-on experience in data science, machine learning, and statistical modeling. Strong expertise in time series forecasting (ARIMA, XGBoost, RandomForest, TFT, NHITS, etc.) and familiarity with deep learning frameworks (TensorFlow, PyTorch). Excellent programming skills in Python (preferred), with proficiency in libraries such as NumPy, Pandas, scikit-learn, and visualization tools (Matplotlib, Seaborn, Plotly). Solid conceptual understanding of machine learning algorithms, deep learning architectures, and statistical methods. Experience with data preprocessing, feature engineering, and model evaluation. Ability to learn quickly and adapt to new technologies, tools, and methodologies. Strong problem-solving skills and a keen attention to detail. Excellent communication and presentation skills. Preferred Qualifications: Experience with cloud platforms and MLOps tools. Exposure to big data technologies (Spark, Hadoop) is a plus. Masters degree in Computer Science, Statistics, Mathematics, or a related field.