32 Decision Tree Jobs

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

Evaluate model development data quality, methodology Perform proper documentation Conduct in-depth analysis of large data sets and support the review and maintenance process of relevant models and model validation documentation. Required Candidate profile 2+ years experience in model development or model validation experience in the retail section of a U. S. financial services/banking hands-on and proven experience utilizing Python, Spark , SAS, SQL,

Skill required: Insight Engine - Analytics Insights Designation: Analytics and Modeling Analyst Qualifications: Any Graduation Years of Experience: 3 to 5 years About Accenture Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. Visit us at www.accenture.com What would you do We are seeking a Machine Learning Data Scientist with 2 to 3 years of hands-on experience to join our growing Insights and Analytics team. The ideal candidate will be proficient in building ML models using supervised and unsupervised learning techniques, comfortable working with Python-based ML libraries, and experienced in data preparation workflows. Familiarity with Microsofts AI/ML ecosystem is a strong advantage. What are we looking for Preferred (Strong Advantage):Hands-on experience with Azure Machine Learning Studio and Automated ML.Familiarity with Azure Cognitive Services for vision, language, and decision tasks.Experience working with Microsoft Fabric and Synapse ML integration. Qualifications:Bachelor s or Masters degree in Computer Science, Data Science, Engineering, or related field.23 years of experience in applied machine learning and data science projects.Solid understanding of model training, validation, and deployment workflows.Experience working with version control (e.g., Git) and collaborative development environments.Nice to Have:Familiarity with tools that help automate and manage the process of building, testing, and deploying machine learning models (MLOps and CI/CD pipelines).Basic understanding of cloud-based architecture and APIs. Roles and Responsibilities: Develop and implement machine learning models using supervised and unsupervised techniques.Apply appropriate machine learning algorithms for prediction tasks (e.g., linear regression, decision trees, neural networks) and data segmentation (e.g., k-means clustering, hierarchical clustering) based on project needs.Perform data preprocessing, feature engineering, and model evaluation.Use Python libraries such as scikit-learn, TensorFlow, and others to build and test models.Analyse and manipulate structured datasets using notebooks (e.g., Jupyter).Collaborate with data engineers, analysts, and product teams to translate business problems into ML solutions.Document model performance, data flows, and process pipelines. Qualification Any Graduation

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

Industry: General Insurance Role Lead Data Scientist Years of Experience 8+ years Purpose of Role In this role, The Candidate should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. To help our company analyze trends to make better decisions. Build propensity models, customer segmentations, uplift models, campaign response models, risk, and fraud detection models. Also, Integrate the models with the business processes and consuming systems via ML Ops processes. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to evaluate the effectiveness of different courses of action. Key Accountabilities Responsibilities will include but will not be restricted to: Create models as required by the business with a high degree of precision and recall. Model accuracy and stability are key accountabilities. Understand business priorities and align data science deliverables to ensure the business receives the intelligence and modeling inputs to drive decisions. Work with stakeholders throughout the organization to identify opportunities for using company data to drive business solutions. Undertake preprocessing of structured and unstructured data and analyze large amounts of information to discover trends and patterns. Assess the effectiveness and accuracy of new data sources and data gathering techniques. Coordinate with different functional teams to implement models and monitor outcomes. Recruit, train, develop and supervise Junior level employees. Develop processes and tools to monitor and analyze model performance and data accuracy. Technical Requirements (what) Proven experience of 8+ years as a Data Scientist. Post Graduate degree in Computer Science, Statistics, Engineering, Physics, Mathematics, Econometrics or MBA with a ML/DS focus. Knowledge of SQL and R or Python; familiarity with Scala & SPARK is an asset. Candidates with experience of working on AWS stack will be preferred, however this is not a compulsory requirement. Knowledge and experience in machine learning, optimization, statistical and data mining techniques- regression, simulation, clustering, decision trees, classification algos (bagging/boosting), neural networks. Desired Personal Qualities or Behavior Strong Analytical critical thinking skills and business acumen Strong commitment to professional development. Process Oriented and excellent time management skills. Ability to adapt to new situations and issues and to solve problems. Good organizational, communication, presentational and people skills - with the capability to communicate concisely and effectively equally well with fellow employees, non-technical colleagues and with members and/or customers alike. Only apply if you are matching with above Criteria Work From Office First and last Saturday will be working 60 and 90 Days Notice periods Please don't apply. Interested candidates can share their resumes at - shubhanshi.agarwal@mounttalent.com 7302239534

Role & responsibilities Develop and implement a comprehensive analytics strategy to support the organization's business objectives. Lead cross-functional projects using advanced data modeling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities. Build, develop and maintain data models, reporting systems, data automation systems, dashboards and performance metrics support that support key business decisions on Microsoft Power BI and Snowflake. Driving key business impacting processes like demand forecast generation and SNOP processes. Generating sales recommendation for trade sales team. Optimizing business process like network, inventory, etc., with data modeling and predicting / prescribing algorithms. Oversee the design and delivery of reports and insights that analyze business functions and key operations and performance metrics. Manage and optimize processes for data intake, validation, mining and engineering as well as modeling, visualization and communication deliverables. Anticipate future demands of initiatives related to people, technology, budget and business within your department and design/implement solutions to meet these needs. Apply advanced analytics techniques to improve commercial routines and processes. Organize and drive successful completion of data insight initiatives through effective management of analyst and data employees and effective collaboration with stakeholders. Communicate results and business impacts of insight initiatives to stakeholders within and outside of the company. Ability to look, analyse, critically think, and communicate insights to support data-driven decisions. Preferred candidate profile With 10+ years of experience in a position monitoring, managing, manipulating and drawing insights from data, and someone with at least 3 years of experience leading a team Experience with data visualization tools: Power BI, Tableau, Raw, chart.js, etc. Experience in understanding and managing the data flow across multiple systems to datawarehouse. Working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple data systems on premises and cloud-based data sources. Understanding of and experience using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units.

Job Title - + + Management Level: Location:Kochi, Coimbatore, Trivandrum Must have skills:Big Data, Python or R Good to have skills:Scala, SQL Job Summary A Data Scientist is expected to be hands-on to deliver end to end vis a vis projects undertaken in the Analytics space. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. Roles and Responsibilities Identify valuable data sources and collection processes Supervise preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns for insurance industry. Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Collaborate with engineering and product development teams Hands-on knowledge of implementing various AI algorithms and best-fit scenarios Has worked on Generative AI based implementations Professional and Technical Skills 3.5-5 years experience in Analytics systems/program delivery; at least 2 Big Data or Advanced Analytics project implementation experience Experience using statistical computer languages (R, Python, SQL, Pyspark, etc.) to manipulate data and draw insights from large data sets; familiarity with Scala, Java or C++ 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 Hands on experience in Azure/AWS analytics platform (3+ years) Experience using variations of Databricks or similar analytical applications in AWS/Azure Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop) Strong mathematical skills (e.g. statistics, algebra) Excellent communication and presentation skills Deploying data pipelines in production based on Continuous Delivery practices. Additional Information Multi Industry domain experience Expert in Python, Scala, SQL Knowledge of Tableau/Power BI or similar self-service visualization tools Interpersonal and Team skills should be top notch Nice to have leadership experience in the past Qualification Experience:3.5 -5 years of experience is required Educational Qualification:Graduation (Accurate educational details should capture)

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

Roles & Responsibilities: Ensure that high quality bio statistical and psychopharmacology support is provided by the Analytics team Ensure that staff implement innovative, rigorous bio statistical methods to meet study objectives Lead RWE (Real World Evidence) large scale analytics (LSA) studies. Run statistical programs in R, R shiny, deploy study packages and generate reliable RWE results in TFLs with minimal supervision. Provide statistical support for design, implementation, running, analysis and dissemination of results for clinical trials Design and analyze clinical research projects Create and execute Statistical Analysis Plans Strong Knowledge in RWE(Real World Evidence) with Bio statistics Background Experience in creating cohort analysis or Meta analysis or Survival analysis or Bayesian Versus Frequentest Approaches to Clinical Trials Experience in implementing generalized mixture models, Bayesian mixer models, Fixed-effects and Random-effects models Knowledge on Statistical Process Control, Stochastic Optimization Knowledgeable in R or Python programming Skills and shiny web app development Knowledge on Cloud platform like AWS Exposure to Healthcare data formats like HL7, OMOP, ODHSI Exposure to RWE, RWA, RWD Experience with data sources like registries, EMR Good communications Skills

Role And Responsibilities : - Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. - Mine and analyze data from company databases to drive optimization and improvement of business strategies. - Assess the effectiveness and accuracy of data sources and data gathering techniques. - Develop custom data models and algorithms to apply to data sets. - Use predictive modelling to increase and optimize business outcomes. - Work individually or with extended teams to operationalize models & algorithms into structured software, programs or operational processes - Coordinate with different functional teams to implement models and monitor outcomes. - Develop processes and tools to monitor and analyze model performance and data accuracy. - Provide recommendations to business users based upon data/ model outcomes, and implement recommendations including changes in operational processes, technology or data management - Primary area of focus: PSCM/ VMI business; secondary area of focus: ICS KPI s - Business improvements pre & post (either operational program, algorithm, model or resultant software). Improvements measured in time and/or dollar savings - Satisfaction score of business users (of either operational program, algorithm, model or resultant software). Qualifications And Education Requirements - Graduate BSc/BTech in applied sciences with year 2 statistics courses. - Relevant Internship (at least 2 months) OR Relevant Certifications of Preferred Skills. Preferred Skills - Strong problem-solving skills with an emphasis on business development. - Experience the following coding languages : - R or python (Data Cleaning, Statistical and Modelling packages) , SQL, VBA and DAX (PowerBI) - Knowledge of working with and creating data architectures. - 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. - Excellent written and verbal communication skills for coordinating across teams. - A drive to learn and master new technologies and technique Compliance Requirements : - GET has a Business Ethics Policy which provides guidance to all employees in their day-to-day roles as well as helping you and the business comply with the law at all times. The incumbent must read, understand and comply with, at all times, the policy along with all other corresponding policies, procedures and directives. QHSE Responsibilities - Demonstrate a personal commitment to Quality, Health, Safety and the Environment. - Apply GET, and where appropriate Client Company s, Quality, Health, Safety & Environment Policies and Safety Management Systems. - Promote a culture of continuous improvement, and lead by example to ensure company goals are achieved and exceeded. Skills - Analytical skills - Negotiation - Convincing skills Key Competencies - Never give up attitude - Flexible - Eye to detail Experience: Minimum 8 Years Of Experience.

Job Information Job Opening ID ZR_1640_JOB Date Opened 13/12/2022 Industry Technology Job Type Work Experience 8-12 years Job Title Sr Technical Lead City Hyderabad Province Telangana Country India Postal Code 500001 Number of Positions 4 Roles & Responsibilities: Ensure that high quality bio statistical and psychopharmacology support is provided by the Analytics team Ensure that staff implement innovative, rigorous bio statistical methods to meet study objectives Lead RWE (Real World Evidence) large scale analytics (LSA) studies. Run statistical programs in R, R shiny, deploy study packages and generate reliable RWE results in TFLs with minimal supervision. Provide statistical support for design, implementation, running, analysis and dissemination of results for clinical trials Design and analyze clinical research projects Create and execute Statistical Analysis Plans Strong Knowledge in RWE(Real World Evidence) with Bio statistics Background Experience in creating cohort analysis or Meta analysis or Survival analysis or Bayesian Versus Frequentest Approaches to Clinical Trials Experience in implementing generalized mixture models, Bayesian mixer models, Fixed-effects and Random-effects models Knowledge on Statistical Process Control, Stochastic Optimization Knowledgeable in R or Python programming Skills and shiny web app development Knowledge on Cloud platform like AWS Exposure to Healthcare data formats like HL7, OMOP, ODHSI Exposure to RWE, RWA, RWD Experience with data sources like registries, EMR Good communications Skills check(event) ; career-website-detail-template-2 => apply(record.id,meta)" mousedown="lyte-button => check(event)" final-style="background-color:#2B39C2;border-color:#2B39C2;color:white;" final-class="lyte-button lyteBackgroundColorBtn lyteSuccess" lyte-rendered=""> I'm interested

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.

Data Analytics Engineer / Data Scientist Location- Mysuru (Preferred) or Remote (India) Full-Time | 3+ Years Experience ABOUT HOPTEKAI: At Hoptek, a Kearney Company, were building AI-powered SaaS products that help trucking companies operate smarter from pricing freight and planning networks to allocating assets and reducing waste. We’re looking for a Data Analytics Engineer / Data Scientist who’s excited to solve hard operations problems, build AI models that get embedded into our products, and help our customers get smarter through data. If you love building applied ML solutions and developing new ideas at the intersection of logistics and optimization, this role is for you. POSITION OVERVIEW: Build machine learning and optimization models to support pricing, routing, and network planning Partner with product and engineering teams to embed AI algorithms into customer-facing software Analyze freight networks and develop insights that drive operational efficiency Use PostgreSQL and Apache Superset to develop internal and customer-facing analytics as needed Prototype innovative solutions to unstructured problems using Python, OR techniques, and statistical methods Understand how customers interact with the platform and develop analytics to support adoption and value delivery What We’re Looking For: 3+ years of experience in data science, analytics engineering, or operations research Proficiency in Python, SQL, and relevant data/ML libraries (e.g., pandas, scikit-learn, XGBoost) Strong grasp of optimization techniques, network models, or decision science Familiarity with data visualization tools — especially Apache Superset Ability to work with real-world, messy logistics data and extract actionable intelligence Curiosity and creativity in approaching open-ended product and analytics challenges Bonus Points For: Experience in transportation, logistics, or freight planning Hands-on experience with graph analytics or geospatial data Experience productionizing ML/OR models within SaaS applications Exposure to pricing algorithms, dynamic optimization, or network simulations Why HOPTEKAI: Applied AI, Real Impact: Your work powers critical product decisions — from what to bid, to where to send the next truck Innovation-Driven: You’ll get to explore new techniques and shape the future of optimization in freight Close Loop from Data to Product: Help us transform ideas into algorithms, and algorithms into product features Mysuru Preferred: Collaborate on-site with our core team — or work remotely within India We’re Hiring Fast: Join a high-impact team at a critical growth moment

Core Characteristics Achievement-oriented Enjoys taking on challenges, even if they might fail. Innovative – Prefers working in unconventional ways or on tasks that require creativity with multivariable inputs and uncertainties. Resource maximizing – Identifies and leverages team resource strengths, while maintaining awareness and pushing for needed growth opportunities. Autonomous/ independent – Enjoys working with little direction. Dynamically detail oriented – Has the awareness of the need and ability to go deep without getting lost, while staying grounded with the bigger picture. Critical thinker – Applies logic, reason, and rationale to a given problem and/ or proposed solution. Dependable – More reliable than spontaneous. Flexible – Ability to manage competing priorities in a fluid environment. Prioritizing – Effective with prioritization, goal setting, and time management. Communicator – Excellent in communications, interpersonally, and in writing. Key Responsibilities: Analyze and interpret complex datasets to uncover valuable insights. Develop and implement Machine Learning (ML) models and algorithms. Collaborate with the team to design and execute data experiments. Utilize cloud platforms for data storage, processing, and analysis. Present findings and insights to both technical and non-technical stakeholders Stay updated on industry trends and advancements in data science, with a focus on healthcare informatics. Analyze complex healthcare data sets to identify trends, patterns, and insights. Create and present reports, dashboards, and visualizations to communicate findings to stakeholders. Isolate healthcare trend drivers and financial impacts associated with client medical claims, pharmacy claims, and other types of healthcare data. Perform varying types of analysis including medical carrier network valuations, discount analysis, and benchmarking. Conduct complex analyses adhering to best practice standards by selecting appropriate data sources, developing assumptions, recognizing considerations, and establishing recommendations. Identify opportunities for process improvement and efficiency through data analysis. Resolve unreasonable results, suboptimal solutions, and data anomalies based on experience and professional judgment. Act as a technical expert and advise on strategic data mining techniques used to identify new relationships or patterns in data. Build predictive models to accurately analyze potential outcomes that are likely costs / savings for a given initiative or event(s). Translate, document, and present approaches, processes, and results of complex modeling and statistical analysis into layperson terms for diverse, internal and external audiences. Qualifications: Degree in computer science, Statistics, Data Science, or a related field. Strong working knowledge of data manipulation and analysis libraries (e.g. Pandas, NumPy, scikit-learn) Familiarity with machine learning (ML) concepts and algorithms. Analyze and interpret complex healthcare datasets to extract valuable insights. Experience with data visualization tools (e.g. Matplotlib, Seaborn, tableau, PowerBI) Basic understanding of databases systems and SQL Experience with cloud platforms (e.g., AWS, Azure or Google Cloud) in a healthcare and biomedical data (ex., clinical and life-sciences) context. Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch) and familiarity with generative AI tools for innovative data-driven solutions. Excellent problem-solving and analytical skills. Eagerness to learn and adapt to new technologies and methodologies. Must possess strong analytical skills with the ability to collect, organize, analyze, and disseminate information with attention to detail and accuracy. Ability to generate information quickly and manage multiple projects at once. Strong analytical skills with the ability to collect, organize, analyze, conceptualize, problem solve, and disseminate information confidently and collaboratively with attention to detail, accuracy, timeliness. Experience in building and deploying highly scalable systems, algorithms, and tools on platforms to support machine learning and deep learning solutions Experience with Azure/AWS tools and technology

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

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Python (Programming Language) Good to have skills : Oracle Procedural Language Extensions to SQL (PLSQL)Minimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Engineer, you will design, develop, and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL processes to migrate and deploy data across systems. Be involved in the end-to-end data management process. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work-related problems.- Develop and maintain data pipelines.- Ensure data quality throughout the data management process. Professional & Technical Skills: - Must To Have Skills: Proficiency in Python (Programming Language).- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 3 years of experience in Python (Programming Language).- This position is based at our Gurugram office.- A 15 years full-time education is required. Qualification 15 years full time education

Data Analytics Engineer / Data Scientist Location- Mysuru (Preferred) or Remote (India) Full-Time | 3+ Years Experience ABOUT KEARNEY: Kearney is a leading global management consulting firm with more than 5,300 people working in more than 40 countries. We work with more than three-quarters of the Fortune Global 500, as well as with the most influential governmental and nonprofit organizations. Kearney is a partner-owned firm with a distinctive, collegial culture that transcends organizational and geographic boundariesand it shows. Regardless of location or rank, our consultants are down to earth, approachable, and have a shared passion for doing innovative client work that provides clear benefits to the organizations we work with in both the short and long term. ABOUT HOPTEKAI: At Hoptek, a Kearney Company, were building AI-powered SaaS products that help trucking companies operate smarter — from pricing freight and planning networks to allocating assets and reducing waste. We’re looking for a Data Analytics Engineer / Data Scientist who’s excited to solve hard operations problems, build AI models that get embedded into our products, and help our customers get smarter through data. If you love building applied ML solutions and developing new ideas at the intersection of logistics and optimization, this role is for you. POSITION OVERVIEW: Build machine learning and optimization models to support pricing, routing, and network planning Partner with product and engineering teams to embed AI algorithms into customer-facing software Analyze freight networks and develop insights that drive operational efficiency Use PostgreSQL and Apache Superset to develop internal and customer-facing analytics as needed Prototype innovative solutions to unstructured problems using Python, OR techniques, and statistical methods Understand how customers interact with the platform and develop analytics to support adoption and value delivery What We’re Looking For: 3+ years of experience in data science, analytics engineering, or operations research Proficiency in Python, SQL, and relevant data/ML libraries (e.g., pandas, scikit-learn, XGBoost) Strong grasp of optimization techniques, network models, or decision science Familiarity with data visualization tools — especially Apache Superset Ability to work with real-world, messy logistics data and extract actionable intelligence Curiosity and creativity in approaching open-ended product and analytics challenges Bonus Points For: Experience in transportation, logistics, or freight planning Hands-on experience with graph analytics or geospatial data Experience productionizing ML/OR models within SaaS applications Exposure to pricing algorithms, dynamic optimization, or network simulations Why Kearney HOPTEKAI: Applied AI, Real Impact: Your work powers critical product decisions — from what to bid, to where to send the next truck Innovation-Driven: You’ll get to explore new techniques and shape the future of optimization in freight Close Loop from Data to Product: Help us transform ideas into algorithms, and algorithms into product features Mysuru Preferred: Collaborate on-site with our core team — or work remotely within India We’re Hiring Fast: Join a high-impact team at a critical growth moment Equal Employment Opportunity and Nondiscrimination HOPTEK, A Kearney Company, prides itself on providing a culture that allows employees to bring their best selves to work every day. Our people can feel comfortable, confident, and joyful to do great things for our firm, our teams, and our clients. HOPTEK, A Kearney Company, aims to build diverse capabilities to help our clients solve their most mission-critical problems. HOPTEK, A Kearney Company, is committed to building a diverse, unbiased, and inclusive workforce. We are an equal opportunity employer; we recruit, hire, train, promote, develop, and provide other conditions of employment without regard to a person’s gender identity or expression, sexual orientation, race, religion, age, national origin, disability, marital status, pregnancy status, veteran status, genetic information, or any other differences consistent with applicable laws. This includes providing reasonable accommodation for disabilities or religious beliefs and practices. Members of communities historically underrepresented in analytics and consulting are encouraged to apply.

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 Overview: We are seeking a talented and driven Machine Learning Engineer to design and optimize machine learning models that will enhance a variety of credit and operational processes. This role will involve building cutting-edge solutions in areas like underwriting, loan processing, fraud detection, and risk mitigation, while continuously driving improvements through innovation and advanced techniques. Key Responsibilities: - Model Development & OptimizationDesign, deploy, and refine machine learning models to support key functions such as underwriting, account management, fraud detection, and loss prevention. - Advanced Techniques ImplementationIdentify opportunities to implement advanced machine learning approaches-such as Natural Language Processing (NLP), Image Recognition, and Graph Mining-to address complex business challenges. - Collaboration & Knowledge SharingWork with internal and external resources, as well as open-source algorithms, to find the best solutions and improve model performance. - Risk Management CompliancePartner with the Model Risk Management team to ensure models are developed with appropriate rigor and align with risk management and governance standards. - Cross-Functional CollaborationCollaborate closely with Product and Engineering teams to ensure seamless model deployment and integration. - Performance MonitoringTrack the effectiveness of models through dashboards and key performance indicators (KPIs), ensuring continuous improvement. - Stakeholder CommunicationPresent model insights and performance reports to key stakeholders in Credit, Risk, and Business Units, making complex findings accessible and actionable. Qualifications: - Educational BackgroundBachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. A Master's degree is highly preferred. - Experience6-12 years of hands-on experience developing and implementing machine learning models in a professional environment. - Technical ProficiencyStrong expertise in SQL and Python, with the ability to write efficient code for working with large datasets and creating advanced features. - Analytical ThinkingExceptional attention to detail and an ability to uncover hidden data patterns through thorough investigation. - Machine Learning ExpertiseSolid foundation in machine learning and statistical modeling, including supervised and unsupervised learning techniques like regression, decision trees, support vector machines, boosting, deep learning, and more. Must stay current with industry advancements to apply the best techniques. - Database KnowledgeProficient in working with SQL, NoSQL, Hive, and other relevant database technologies. - Effective CommunicationStrong ability to translate complex technical concepts into clear, understandable terms for non-technical stakeholders. Apply Save Save Pro Insights

Evaluate model development data quality, methodology Perform proper documentation Conduct in-depth analysis of large data sets and support the review and maintenance process of relevant models and model validation documentation. Required Candidate profile 2+ years experience in model development or model validation experience in the retail section of a U. S. financial services/banking hands-on and proven experience utilizing Python, Spark , SAS, SQL,

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

Skill required: Insight Engine - Analytics Insights Designation: Analytics and Modeling Analyst Qualifications: Any Graduation Years of Experience: 3 to 5 years What would you do? We are seeking a Machine Learning Data Scientist with 2 to 3 years of hands-on experience to join our growing Insights and Analytics team. The ideal candidate will be proficient in building ML models using supervised and unsupervised learning techniques, comfortable working with Python-based ML libraries, and experienced in data preparation workflows. Familiarity with Microsoft's AI/ML ecosystem is a strong advantage. What are we looking for? Preferred (Strong Advantage): Hands-on experience with Azure Machine Learning Studio and Automated ML. Familiarity with Azure Cognitive Services for vision, language, and decision tasks. Experience working with Microsoft Fabric and Synapse ML integration. Qualifications: Bachelor s or Master's degree in Computer Science, Data Science, Engineering, or related field. 2–3 years of experience in applied machine learning and data science projects. Solid understanding of model training, validation, and deployment workflows. Experience working with version control (e.g., Git) and collaborative development environments.Nice to Have: Familiarity with tools that help automate and manage the process of building, testing, and deploying machine learning models (MLOps and CI/CD pipelines). Basic understanding of cloud-based architecture and APIs. Roles and Responsibilities: Develop and implement machine learning models using supervised and unsupervised techniques. Apply appropriate machine learning algorithms for prediction tasks (e.g., linear regression, decision trees, neural networks) and data segmentation (e.g., k-means clustering, hierarchical clustering) based on project needs. Perform data preprocessing, feature engineering, and model evaluation. Use Python libraries such as scikit-learn, TensorFlow, and others to build and test models. Analyse and manipulate structured datasets using notebooks (e.g., Jupyter). Collaborate with data engineers, analysts, and product teams to translate business problems into ML solutions. Document model performance, data flows, and process pipelines. Qualification Any Graduation