136 Data Scientist Jobs - Page 3

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Experience: 7-12years Location and Work Mode: Pune Job Description: About this Role We are seeking a highly skilled and motivated Data Scientist to join our team. This role is ideal for individuals who are passionate about leveraging data to drive innovation and create intelligent, scalable solutions. The successful candidate will work across a variety of data science domains, including diagnostic, predictive, and prescriptive analytics, and will contribute to the development of autonomous cognitive systems. This is an exciting opportunity to be part of a forward-thinking team that values continuous learning and collaboration. Who are you A data enthusiast with a strong foundation in machine learning, deep learning, and statistical modelling. A collaborative problem-solver who thrives in cross-functional teams and is comfortable engaging with stakeholders. A continuous learner with a passion for exploring new tools, technologies, and methodologies. An effective communicator who can translate complex data insights into actionable business strategies. A self-starter with a proactive mindset and the ability to work independently in a dynamic environment. What you will do Manage and process large-scale data on both on-premise and cloud platforms (preferably AWS). Design and implement diagnostic models using decision theory and causal inference techniques (e.g., DAG, ADMG, Deterministic SME). Build and productise diagnostic systems for scalable reuse across the organisation. Develop robust predictive and prescriptive analytics models using AI techniques such as ML, DL, NLP, ES, and RL. Create intelligent systems that determine the Next Best Action based on prescriptive analytics. Drive the development of autonomous cognitive systems that proactively recommend actions with minimal human intervention. Apply advanced deep learning techniques including CNNs, RNNs, and MLPs to solve complex business problems. Utilise machine learning and deep learning libraries such as TensorFlow, PyTorch, Scikit-learn, NumPy, Pandas, Statsmodels, Theano, and XGBoost. Collaborate with stakeholders to understand business needs and deliver data-driven solutions. Present insights and findings using visualisation tools like Tableau and Power BI. What skills you need Proficiency in programming languages: Python, R, SQL Experience with frameworks: TensorFlow, Keras, Scikit-learn Strong understanding of statistical modelling: regression, classification, clustering, time series Hands-on experience with cloud platforms: AWS (preferred), Azure Familiarity with big data technologies and environments Excellent communication and stakeholder management skills Strong analytical and problem-solving abilities At least one certification in AWS is preferred What skills you will learn Advanced applications of causal inference and decision theory in real-world scenarios Building and deploying scalable AI systems in cloud environments Designing autonomous systems that integrate feedback loops for continuous learning Enhancing stakeholder engagement through data storytelling and visualisation Exposure to cutting-edge tools and frameworks in the AI and ML ecosystem

Experience: Minimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role. Proven experience in banking or financial services is highly preferred. Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark). Experience in Azure ML tools: Databricks etc. Experience with end-to-end model lifecycle management and MLOps. Minimum Qualification: Masters Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.

Notice Period : Immediate - 15 Days About the Role : We are seeking a highly skilled Senior Data Scientist to join our team and contribute to cutting-edge projects. As a key member of our data science team, you will leverage your expertise in machine learning, natural language processing, and data engineering to develop innovative solutions that drive business value. Responsibilities : - Machine Learning Model Development : Design, develop, and deploy advanced machine learning models, focusing on natural language processing tasks such as text classification, sentiment analysis, and language generation. - Data Engineering : Extract, transform, and load (ETL) data from various sources, ensuring data quality and consistency. - NLP Techniques : Apply state-of-the-art NLP techniques, including language models and text processing, to solve complex problems. - Python and ML Frameworks : Utilize Python programming language and popular ML frameworks like PyTorch or TensorFlow to build efficient and scalable models. - Cloud and Containerization : Leverage cloud platforms (GCP, AWS) and containerization technologies (Docker) for efficient deployment and management of ML models. - Database Management : Work with relational databases (Postgres, MySQL) to store, manage, and query large datasets. - Knowledge Graphs and ML Publications : Contribute to the development of knowledge graphs and stay updated with the latest advancements in the field through research and publications. Qualifications : Experience : 4-7 years of hands-on experience in data science, with a strong focus on machine learning and natural language processing. Technical Skills : - Proficiency in Python programming language. - Deep understanding of machine learning algorithms and techniques. - Expertise in NLP, including language models and text processing. - Familiarity with ML frameworks like PyTorch or TensorFlow. - Experience with cloud platforms (GCP, AWS) and containerization (Docker). - Knowledge of relational databases (Postgres, MySQL). Soft Skills : - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Ability to work independently and as part of a team.

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.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Working Hours : 2PM to 11PM IST Mid-Level ML Engineers / Data Scientist Role : (4-5 years of experience ) - Experience processing, filtering, and presenting large quantities (100K to Millions of rows) of data using Pandas and PySpark - Experience with statistical analysis, data modeling, machine learning, optimizations, regression modeling and forecasting, time series analysis, data mining, and demand modeling. - Experience applying various machine learning techniques and understanding the key parameters that affect their performance. - Experience with Predictive analytics (e.g., forecasting, time-series, neural networks) and Prescriptive analytics (e.g., stochastic optimization, bandits, reinforcement learning). - Experience with Python and Python packages like NumPy, Pandas and deep learning frameworks like TensorFlow, Pytorch and Keras - Experience in Big Data ecosystem with frameworks like Spark, PySpark , Unstructured DBs like Elasticsearch and MongoDB - Proficiency with TABLEAU or other web-based interfaces to create graphic-rich customizable plots, charts data maps etc. - Able to write SQL scripts for analysis and reporting (Redshift, SQL, MySQL). - Previous experience in ML, data scientist or optimization engineer role with a large technology company. - Experience in an operational environment developing, fast-prototyping, piloting, and launching analytic products. - Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations. - Experience in creating data driven visualizations to describe an end-to-end system. - Excellent written and verbal communication skills. The role requires effective communication with colleagues from computer science, operations research, and business backgrounds. - Bachelors or Masters in Artificial Intelligence, Computer Science, Statistics, Applied Math, or a related field.

• Proficiency in Python and SQL for data extraction, manipulation, and analysis • Exploratory data analysis (EDA), developing, and deploying machine learning models • Expertise in deploying ML models on cloud platforms such as AWS or Azure

Job Title: Data Scientist(5 Positions)/ Lead OR Manager -Data Scientist (3 positions) Experience: Data scientist (8-10 years) / Lead Data scientist(14+ years) Job Location: Whitefield, Bangalore Mode of working: Hybrid Interview Process: First Round: L1-Internal interview Second Round: Assessment shared by us needs to be completed in 48 hours Third Round: Client discussion over the submitted assessment. Final Round: HR Discussion Preferred Domain: Healthcare Insurance/ Insurance agencies / Health Insurance / Any Insurance We are looking for a talented Data Scientist to join our growing team. In this role, you will lead efforts to develop, enhance, and optimize advanced AI and machine learning models with a particular focus on Generative AI, Large Language Models (LLMs), Langchain, and Prompt Engineering. You will oversee the application of statistical modeling techniques to derive insights, build models, and lead research initiatives that push the boundaries of AI technologies. Key Responsibilities: Leadership & Collaboration: Lead a team of data scientists, researchers, and engineers working on high-impact projects related to generative models, NLP, and statistical modeling. Collaborate with cross-functional teams, including engineering, product management, and research, to deliver AI-powered products and solutions. Generative AI Development: Spearhead the development and deployment of Generative AI models and algorithms to address complex problems in areas like content generation, conversational AI, and creative automation. LLM Implementation & Optimization: Develop, fine-tune, and optimize large language models (LLMs) for diverse applications, ensuring they are robust, scalable, and accurate in real-world scenarios. Langchain Integration: Design and integrate Langchain for managing and deploying sophisticated language models with a focus on complex workflows, multi-agent systems, and real-time applications. Prompt Engineering: Lead prompt engineering efforts to optimize AI models' output quality, improve interactions, and enable more effective natural language understanding across a variety of use cases. Statistical Modeling: Utilize advanced statistical techniques to analyze and interpret data, build predictive models, and solve business-critical challenges through data-driven insights. Research & Innovation: Stay ahead of trends in AI and ML, particularly in the fields of NLP, LLMs, and generative models. Drive innovation by exploring cutting-edge techniques and methodologies in the AI space . Mentorship & Knowledge Sharing: Mentor junior team members and promote a collaborative, learning-oriented environment. Share knowledge and foster an atmosphere of continuous improvement within the data science team. Performance Optimization: Ensure model performance meets or exceeds company and client expectations by identifying areas of improvement, testing new methods, and scaling the systems accordingly. Ethical AI Development: Advocate for and implement ethical considerations in the development and deployment of AI models, including fairness, transparency, and privacy. Qualifications: Required: Education: Ph.D. or Masters degree in Computer Science, Data Science, Mathematics, Statistics, or related field, or equivalent practical experience. Experience: 8+ years of experience in data science, with at least 2-3 years in a leadership role. Proven expertise in Generative AI, particularly in areas like content generation, deep learning, and language modeling. Strong background in Large Language Models (LLMs) such as GPT, T5, BERT, or similar architectures. Hands-on experience with Langchain for building NLP workflows, pipelines, and integrating external systems with LLMs. Hands-on experience of Prompt Engineering, including techniques to refine and optimize outputs for various NLP tasks. Expertise in statistical modeling and quantitative analysis, with the ability to apply techniques to solve real-world problems. Preferred: Experience working with transformer models and fine-tuning LLMs for specific tasks. Expertise in AI model evaluation and metrics (e.g., BLEU, ROUGE, perplexity). Background in developing AI-driven products from concept to deployment. Strong publication record in AI research, particularly in NLP and machine learning . Used cases( Any of them) Automated Underwriting. Customer experience enhancement. Fraud detection . Predictive analytics. Accelerated claims processing. Risk assessment and premium calculation . Customer profiling . c ustomer segmentation . Credit Risk Assessment . Personalised marketing . Anti-Money Laundering (AML) . Personalized patient care. Medical training and simulations. Medical Data Analysis. Please share your updated resume at renuka.rathi@puresoftware.com

Job Description Design and develop machine learning models tailored to mechanical engineering challenges, including predictive modelling, simulation optimisation, and failure analysis. Utilise deep learning and other advanced ML techniques to improve the accuracy and efficiency of CAE simulations. Preprocess and analyse large datasets from CAE simulations, experimental tests, and manufacturing processes for modelling. Train, validate, and fine-tune machine learning models using real-world engineering data. Optimise models for performance, scalability, and robustness in production environments. Collaborate with CAE engineers to integrate ML models into existing simulation workflows (e.g., FEA, CFD, structural analysis). Automate repetitive simulation tasks and enable predictive analytics for design optimisation. Work closely with mechanical engineers, data scientists, and software developers to identify business challenges and develop data-driven solutions. Deploy machine learning models into production environments and monitor their performance. Maintain and update models to ensure reliability and continuous improvement. Stay abreast of the latest advancements in machine learning, AI, and CAE technologies. Apply innovative approaches to solve complex engineering problems. Requirements Bachelors or Master’s degree in Mechanical Engineering, Computer Science, or a related field Proven 2-3 years of experience in developing and deploying machine learning models, preferably in mechanical engineering or CAE domain Hands-on experience with CAE tools such as ANSYS, Abaqus, or similar FEA/CFD software Strong programming skills in Python, R, or Java Proficiency in machine learning frameworks (TensorFlow, PyTorch, scikit-learn) Experience with data preprocessing, feature engineering, and statistical analysis Solid understanding of mathematics, statistics, and problem-solving skills Excellent analytical thinking and ability to tackle complex engineering challenges Strong communication and teamwork skills to collaborate across disciplines Preferred: Experience with physics-informed machine learning and digital twin technologies Preferred: Familiarity with automation of CAE workflows and predictive modelling for product design Benefits Challenging job and a chance to team up with a young and dynamic professional group Chance to build yourself as WE grow. Remuneration that stays competitive and attractive to retain the best. Opportunity to join an organization experiencing year on year growth.

Hi all, We are hiring for the role Data Scientist AI ML Experience: 6 -9 Years Location: Bangalore Notice Period: Immediate - 15 Days Skills: We are looking for a Data Scientist to lead data-driven solutions across our business, from exploratory analysis, incremental hypothesis validation, model development, deployment and monitoring. Skills Needed: Strong knowledge of Applied AI ML & Deep Learning Data Science techniques, Hardcore in ANN /Deep Learning /Machine Learning/NLP Deep knowledge about machine learning algorithms such as tree-based methods, clustering, regression and classification, dimension reduction techniques, linear regression, Logistic regression, k-means, time series forecasting, Hypothesis testing (ANOVA, t-test, etc.), random forest, SVMs, Naive Bayes, gradient boosting, kNN, Deep learning algorithms like CNN, ANN and Reinforcement learning, Anomaly detection. In-depth understanding of Statistical concepts e.g. Probability distributions, statistical tests, correlation analysis, descriptive statistics, kernels, ROC, F1-Score etc. Advanced coding experience in at least one programming language (Python, Pyspark) & Strong experience in object-oriented concepts. Good to have advanced experience in one or more of the following: Spark, Databricks, Azure technical stack Good to have experience in model deployment to cloud/on-prem. Good Communication & presentation skills. If you are interested drop your resume at mojesh.p@acesoftlabs.com Call: 9701971793

Design & develop end-to-end machine learning models & GenAI workflows Fetch & process data from BigQuery & various sources for model development Build & deploy models using Python & frameworks like Scikit Learn, XGBoost/CatBoost, TensorFlow & Gemini Required Candidate profile 4+ years of experience in the Data Science domain and should have hands on exp in Python, Machine Learning and/or Generative AI (Artificial Intelligence) This is an Individual contributor role

Our client is a India's marquee global technology company. They are an international flag-bearer of technical and managerial excellence. With offices around the globe, the company has a comprehensive presence across multiple segments of the IT product and service industries. We are Seeking to identify a Data Scientist Engineer role, responsible for Leading the design, development, and deployment of advanced machine learning models and algorithms. Software engineering experience with Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and generative AI libraries., Understanding of C++ programming principles. Lead the design, development, and deployment of advanced machine learning models and algorithms. Train and fine-tune generative models on large datasets, optimizing model performance and efficiency. Experience of developing and deploying solutions on Nvidia or Intel software stacks will be an added advantage. Excellent problem-solving skills and the ability to work on complex, unstructured challenges. Proficient Understanding of distributed Computing Principles. Working knowledge of frameworks such as accelerate, deepspeed, etc. Experience with hiring, mentoring and leading teams of ML engineers, data engineers, etc. Conduct in-depth data analysis, feature engineering, and data pre-processing to extract meaningful insights. Develop and execute data strategies to collect, process, and store data effectively. Work closely with data engineers and architects to ensure data availability and quality. Collaborate with cross-functional teams to develop AI-powered solutions that address business challenges and opportunities. Ensure the successful integration of AI models into production systems. Stay up-to-date with the latest trends and advancements in data science and AI. Drive research initiatives to explore and implement innovative techniques and technologies. Lead research initiatives to develop novel AI techniques and technologies. Communicate findings, insights, and project progress to non-technical stakeholders in a clear and understandable manner. Publications or contributions to the field of CV, NLP or generative AI are a plus. Your Profile: An Engineer with 5+ years of experience in Leading the design, development, and deployment of advanced machine learning models and algorithms. Understanding of C++ programming. Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and generative AI libraries.

Lead the design, development, and deployment of advanced machine learning models and algorithms. Train and fine-tune generative models on large datasets, optimizing model performance and efficiency. Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and generative AI libraries., Understanding of C++ programming principles. Experience of developing and deploying solutions on Nvidia or Intel software stacks will be an added advantage. Excellent problem-solving skills and the ability to work on complex, unstructured challenges. Proficient Understanding of distributed Computing Principles. Working knowledge of frameworks such as accelerate, deepspeed, etc. Experience with hiring, mentoring and leading teams of ML engineers, data engineers, etc. Conduct in-depth data analysis, feature engineering, and data preprocessing to extract meaningful insights. Develop and execute data strategies to collect, process, and store data effectively. Work closely with data engineers and architects to ensure data availability and quality. Collaborate with cross-functional teams to develop AI-powered solutions that address business challenges and opportunities. Ensure the successful integration of AI models into production systems. Stay up-to-date with the latest trends and advancements in data science and AI. Drive research initiatives to explore and implement innovative techniques and technologies. Lead research initiatives to develop novel AI techniques and technologies. Communicate findings, insights, and project progress to non-technical stakeholders in a clear and understandable manner. Publications or contributions to the field of CV, NLP or generative AI are a plus.

LLMs - OpenAI, Gemini, CoPilot etc. Good Knowledge of RAG Pipeline Architectures Fine/Prompt/Instruction Tuning of LLMs machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn). cloud services (GCP, Azure, AWS).

DS Key Responsibilities Combine expertise in mathematics statistics computer science and domain knowledge to create AIML models to solve various business challenges Collaborate closely with the AI Technical Manager and GCC Petro technical professionals and data engineers to integrate models into the business framework Identify and frame opportunities to apply advanced analytics modeling and related technologies to data to help businesses gain insight and improve decision making workflow and automation Understand and communicate the value of proposed opportunity with team members and other stakeholders Identify needed data and appropriate technology to solve identified business challenges Clean data and develop and test models Establish the life cycle management process for models Provide technical mentoring in modeling and analytics technologies the specifics of the modeling process and general consulting skills Drive innovation in AIML to enhance capabilities in data driven decision making Aligns with team on shared goals and outcomes recognizes others contributions and work collaboratively seek diverse perspectives Takes actions to develop self and others beyond existing skillset Encourages innovative ideas adapts to change and changing technologies Understand and communicate data insights and model behaviors to stakeholders with varying levels of technical expertise Required Qualification Minimum 5 years of experience in designing and developing AIML models and or various optimization algorithms 5 to 9 years of experience Solid foundation in mathematics probability and statistics with demonstrated depth of knowledge and experience in advanced analytics and data science methodologies eg supervised and unsupervised learning statistics data science model development Proficiency in Python and working knowledge of cloud AIML services Azure Machine Learning and Databricks preferred Domain knowledge relevant to the energy sector and working knowledge of Oil and Gas value chain eg upstream midstream or downstream and associated business workflows Proven ability to frame data science opportunities leverage standard foundational tools and Azure services to perform exploratory data analysis for purposes of data cleaning and discovery visualize data and identify actions to reach needed results Ability to quickly assess current state and apply technical concepts across cross functional business workflows Experience with driving successful execution deliverables and accountabilities to meet quality and schedule goals Ability to translate complex data into actionable insights that drive business val Demonstrated ability to engage and establish collaborative relationships both inside and outside immediate workgroup at various organizational levels across functional and geographic boundaries to achieve desired outcomes Demonstrated ability to adjust behavior based on feedback and provide feedback to other Team oriented mindset with effective communication skills and the ability to work collaboratively Strong problem solving skills and attention to detail Excellent communication and collaboration skills

Job Title: Data Scientist Electric Load Forecasting Location: Mumbai / Pune Job Type: Full-time Experience: 3-5 years About the Role: We are seeking a highly motivated Data Scientist – Forecasting with a strong passion for energy, technology, and data-driven decision-making. In this role, you will be responsible for developing and refining energy load forecasting models , analyzing customer demand patterns , and improving forecasting accuracy using advanced time series analysis and machine learning techniques . Your insights will directly support risk management, operational planning, and strategic decision-making across the company. If you thrive in a fast-paced, dynamic environment and enjoy solving complex data science challenges , we’d love to hear from you! Key Responsibilities: Develop and enhance energy load forecasting models using time series forecasting , statistical modeling , and machine learning techniques . Analyze historical and real-time energy consumption data to identify trends and improve forecasting accuracy. Investigate discrepancies between forecasted and actual energy usage , providing actionable insights. Automate data pipelines and forecasting workflows to streamline processes across departments. Monitor day-over-day forecast variations and communicate key insights to stakeholders. Work closely with internal teams and external vendors to refine forecasting methodologies . Perform scenario analysis to assess seasonal patterns, anomalies, and market trends. Continuously optimize forecasting models , leveraging techniques like ARIMA, Prophet, LSTMs, and regression-based models . Qualifications & Skills: 3-5 years of experience in data science, preferably in energy load forecasting , demand prediction, or a related field. Strong expertise in time series analysis , forecasting algorithms , and statistical modeling . Proficiency in Python , with experience using libraries such as pandas, NumPy, scikit-learn, statsmodels, and TensorFlow/PyTorch . Experience working with SQL and handling large datasets. Hands-on experience with forecasting models like ARIMA, SARIMA, Prophet, LSTMs, XGBoost, and random forests . Familiarity with feature engineering, anomaly detection, and seasonality analysis . Strong analytical and problem-solving skills with a data-driven mindset . Excellent communication skills, with the ability to translate technical findings into business insights . Ability to work independently and collaboratively in a fast-paced, dynamic environment . Strong attention to detail, time management, and organizational skills. Preferred Qualifications (Nice to Have): Experience working with energy market data, smart meter analytics, or grid forecasting . Knowledge of cloud platforms (AWS) for deploying forecasting models . Experience with big data technologies such as Spark or Hadoop .

* 6-10 years of total DS and model development experience * A passion for writing high-quality code (Python), and the code should be modular, scalable, and end-end project execution while planning an active hands-on role * Having good problem-solving skills is essential, and it is equally important to have in-depth knowledge to solve complex problems effectively. * Comprehensive knowledge of the regression and classification concepts and mathematical backend along with SQL * Experience in Time Series Forecasting Idea about other machine learning techniques (clustering, regression, ensemble learning, neural nets, time series, optimizations etc.) to their real-world problems * Encourage collaboration with various stakeholders and take complete ownership of deliverables. * Adept understanding of various data science approaches, machine learning algorithms, and statistical methods. Excellent communication skills with presentability, articulation, storytelling capability, and ability to manage complex client situations * Effective mentoring of a team with expertise in industry/domain/functional areas

Responsibilities Job Title: Lead Analyst - Data Science (Intermediate/Senior)Role Summary: We are looking for candidates to build and implement analytics solutions to our esteemed clients. The incumbent should have strong aptitude for numbers, experience in any domain and willingness to learn some cutting edge technologies Technical and Professional Requirements: Other key to have Skills: SQL knowledge and experience working with relational databases. Understanding of any one of domain (Eg: Retail, Supply chain, Logistics, Manufacturing). Understanding of the project lifecycles: waterfall and agile. Soft Skills: Strong verbal and written communication skills with the ability to work well in a team. Strong customer focus, ownership, urgency and drive. Ability to handle multiple, competing priorities in a fast-paced environment. Work well with the team members to maintain high credibility Work Experience: Overall 6-8 of years of experience in Data Analytics, Data Science and Machine Learning. Educational Requirements (any of the following): Bachelor of Engineering/Bachelor of Technology in any stream with consistent academic track record. Bachelor's degree in a quantitative discipline (e.g., Statistics, Economics, Mathematics, Marketing Analytics) or significant relevant coursework with consistent academic track record. Preferred Skills: Technology->Data Science->Machine Learning Additional Responsibilities: Additional Academic Qualification (good to have): Masters in any area related to Science, Mathematics, Statistics, Economy and Finance with consistent academic track record. PhD in any stream.Location: Bangalore, Pune, Hyderabad, Chennai, Trivandrum, Mysore Educational Requirements MCA,MSc,Bachelor of Engineering,BBA,BCom Service Line Data & Analytics Unit * Location of posting is subject to business requirements

Job Summary: We are seeking a skilled Data Scientist with experience in both Python and SAS to join our high-performing analytics team. The ideal candidate will be adept at developing predictive models, analyzing large datasets, and delivering actionable insights using modern data science tools and platforms. Key Responsibilities: Design and develop machine learning and statistical models using Python and SAS. Conduct data exploration, preprocessing, and analysis on structured and unstructured datasets. Use SAS (Base, Advanced, Enterprise Guide, Visual Analytics, or SAS Viya) for reporting, data preparation, and statistical modeling as required. Work with large-scale datasets using Python libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow. Translate business requirements into technical solutions in collaboration with cross-functional teams. Build data pipelines and automate workflows for data analysis and model deployment. Present data-driven insights through visualizations using tools such as Seaborn, Plotly, Matplotlib, or SAS VA. Document models, code, and methodologies for reproducibility and auditability. Qualifications: 2-10 years of experience in data science, machine learning, or advanced analytics. Proficient in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, etc.) and SAS (Base, Advanced, DI, VA, or Viya). Strong knowledge of SQL and experience working with relational databases. Solid foundation in statistical analysis, hypothesis testing, regression, classification, clustering, etc. Experience in building, evaluating, and deploying predictive models. Excellent communication skills and ability to convey complex findings to non-technical stakeholders. Preferred Qualifications : Experience with big data tools (Spark, Hive, Hadoop). Exposure to MLOps tools (MLflow, Airflow, Docker, etc.). Familiarity with cloud platforms (AWS, Azure, GCP). Understanding of SAS integration with cloud or open-source tools. Experience with NLP, image recognition, or deep learning frameworks. Location- Pan ,Delhi NCR,Bengaluru,Chennai,Pune,Kolkata,Ahmedabad,Mumbai, Hyderabad Education- Bachelor's degree in Computer Science, Information Technology, or a related field.

DO NOT APPLY WITHOUT UNDERSTANDING THE ENTIRE JOB DESCRIPTION We are Hiring a Senior Data Scientist for a Leading Fortune 500 Manufacturing Brand Location: Mumbai Experience: Minimum 8 years in Data Science - AI/ML Education: M.E / M.Tech in Computer Science/ IT/ Data Science/ with persuasion of PhD Job Description: - Sr. Data Scientist will be required to build hypothesis, research, prototype, design, develop, and help implement enterprise level ML/ AI/Gen AI models for projects to transform and improve companys business results and competitive position & ensure alignment to the overall digital, data & AI strategy and current and future business objectives. Contribution to Data & AI Platform and Products Work within Digital Data AI Team in development of data science & AI capabilities and features to support delivery on defined objectives around platform aspects Design, implement, and evolve robust, secure and quality solutions that operate for the business ecosystem. Research, design & development of High-Quality Data, AI and analytical systems Define exploratory data analysis (EDA) keeping in line with problem necessities Ensure the development of quality procedures and standards products and supervising tests. Work on various data correction problems such as data cleansing, sourcing and integrating from multiple platforms to make the good data available for data analysis , data science & AI development Provide and help deliver the Solutions Hands on contribution to provide solutions and POCs , working in cross- functional or agile teams to develop and deliver significant aspects of the models and systems. Lead and mentor junior data scientists and ensure availability of necessary data and analysis as needed by business requirement and use cases. Conduct diagnostic across existing data and make future state recommendations in regular intervals. Collaborate with Business Analyst, Data scientists, Data Engineers and Data Analysts to ensure understanding and alignment between business needs and technical implementation. Monitor performance of existing solutions across use cases to identify and drive optimization. Oversee and Research, develop and analyse NLP, Gen AI , computer vision algorithms in Various use cases. Ensure model robustness, model generalization, accuracy, testability, and efficiency. Write product or system development code. Contributing via understanding of machine learning techniques and algorithms, including clustering, anomaly detection, optimization, neural network etc Responsible for deploying AI/ML models (ML Ops) in standalone and cloud based systems and services. Support Projects and Initiatives Help in Collaboration with business unit heads and corporate functions to identify and assist in providing data analysis support across different projects Identify data from legacy systems, to build new solutions based on requirement Provide necessary technical support in new and ongoing digital initiatives to ensure seamless data solutioning. Requisite Experience Essential Minimum 10 Yrs with of experience in data analytics & data science, building, and maintaining various ML models. Good know how of emerging small and larger models 3 to 5 + years of experience in each of the Data Science specialization like NLP, Demand Forecasting, ML Ops Should be able to present portfolio of data science work or use cases Preferred Sound understanding of Data analysis to support the preparatory work Experience working in the agile Environment. Know how/ Familiarity in all aspects of MLOps (source control, continuous integration, deployments, etc.) Experience/ Exposure with Cloud data services like AWS or Azure Special Skills Required Functional: Excellent understanding of machine learning techniques and algorithms, including clustering, anomaly detection, optimization, neural network etc. Strong hands-on coding skills in Python, processing large-scale data set and developing machine learning models. Experience programming in Python, R, and SQL Expertise in developing ML models and deployment of the same Hands on working on developing NLP models using transformers and computer vision. Know-how of deploying AI/ML models (ML Ops) in standalone and cloud-based systems and services. Comfortable working with DevOps: Jenkins, Bitbucket, CI/CD SQL Server experience required Understanding of, dimensional data modelling, structured query language (SQL) skills, data warehouse and reporting techniques Data Governance & Ethics Leadership: Strong analytical skills, ability to ask right questions, analyse data and draw conclusion by making appropriate assumptions, to solve and model complex business requirements Ability to lead team of junior data scientists, get into the details of the problem and ability to code the solution hands on as and when needed Planning & Organizing Present complex data analysis in consumable way and Engage the stakeholders Ability to collaborate with different teams and clearly communicate solutions to both technical and non-technical team members Team player

Position Title: Data Scientist Job Summary We are seeking a Data Scientist to develop and implement data-driven, AI-powered solutions across the organization. In this role, you will apply analytical, statistical, and programming expertise to clean, aggregate, and interpret large datasets translating complex information into actionable insights. You will leverage machine learning algorithms, generative AI (Gen AI), and Retrieval Augmented Generation (RAG) methodologies to drive innovation, inform strategic decisions, and eHectively communicate findings to both technical and non-technical stakeholders.

Position: Lead Data Scientist (Agentic Ai) Location: Chennai Reporting to: Associate Director Job Summary: As a Technical Lead for Agentic AI Workflow Development, you will be responsible for designing, developing, and implementing advanced AI-driven workflows. You will lead a team of developers and collaborate with cross-functional teams to deliver high-quality solutions that meet business needs. Job Description: - Lead the end-to-end development of Agentic AI workflows, including Autogen, Llama, and Langgraph integration. - Design and implement solutions using large language models (LLMs) such as ChatGPT, Gemini, and Llama. - Develop and maintain scalable architectures on hyperscaler platforms (Azure, AWS, Google Cloud). - Utilize Python for backend development and automation tasks. - Ensure effective database management with a strong understanding of both SQL and NoSQL databases. - Troubleshoot and resolve technical issues in a timely manner. - Oversee the orchestration of jobs, including queuing and load balancing for optimal performance. - Collaborate with stakeholders to identify and implement real-world use cases, focusing on document-related solutions and agent interactions. - Mentor and guide junior developers, fostering a culture of continuous learning and improvement. Profile Description: - Bachelor’s degree in Computer Science, Engineering, or a related field; Master’s degree preferred. - Proven experience as a Technical Lead or similar role in AI/ML development. - Strong proficiency in Python and experience with relevant libraries and frameworks. - In-depth knowledge of large language models (LLMs) and their applications. - Experience with hyperscaler architectures (Azure, AWS, Google Cloud). - Solid understanding of SQL and NoSQL databases, with hands-on experience in database design and management. - Excellent troubleshooting skills and the ability to solve complex technical problems. - Demonstrated experience in developing and deploying at least three real-world use cases involving document processing, auto agents, and orchestration. - Strong communication and leadership skills, with the ability to work collaboratively in a team environment. - Familiarity with AI frameworks and tools related to workflow automation. - Experience with containerization and orchestration tools (e.g., Docker, Kubernetes). - Knowledge of CI/CD practices and tools.

job position - vertex AI support engineer experience -- 5 - 9 Years location - Bangalore ( relocation candidate also can apply ) notice period - only immediate joiner can apply ( only serving notice period max - 20 June 2025 ) shift - rotational shift employment type - permanents with brainworks business solution mandatory skills - Vertex AI , Python ,GCP services - , ML/AI -, SQL interested candidate please share your CV's on rutuja.s@bwbsol.com / 9850368787