Sr. Data Scientist_MPIN

Role and Responsibilities

• Working with stake holders from different business units to identify the business opportunities for leveraging the data to drive business solutions.
• Must have good knowledge of advanced statistical methods (automotive or manufacturing domain will be an added advantage). Mine and analyze data, applying statistical methods as necessary, discover the hidden patterns and viewing experiences to identify critical data insights.
• Develop customized ML/AI algorithms for the customers so that they are suited 100% to the requirements
• Develop reusable AI/GenAI/ML/Statistical models that can be scaled to multiple businesses with minimum customization.
• Translate analytic insights into concrete, actionable recommendations for business or product improvement.
• Partner closely with product and engineering leaders throughout the lifecycle of project. Ensure that necessary data is captured analytic needs are well-defined up front and coordinate the analytic needs.
• Independently handle the products/projects and provide technical directions to the other team members.
• Develop dashboards using software like PowerBI to share algorithm results to end users
• Strong interpersonal and communication skills: ability to tell a clear, concise, actionable story with data, to folks across various levels of the company.
• Technical directions to junior in team, like to sort the respective task for appropriate team members, mentoring them technically etc.

Qualifications

Masters from a reputed Indian institutes in the area of Statistics, Machine Learning, Computer Science, etc.

Additional Information

Technical Skills

Must Have

• Strong expertise in

  Python

  and key data science libraries (e.g., pandas, NumPy, scikit-learn, PyTorch/TensorFlow/Keras).
• Proven experience in

  classical ML algorithms

  - regression, classification, clustering, decision trees, random forests, SVMs, neural networks, etc.
• Solid grounding in

  statistical analysis and hypothesis testing

  (DOE, forecasting, segmentation, uncertainty analysis, etc.).
• Hands-on experience with

  data preprocessing

  , feature engineering, imputation, cleansing, transformation, and data exploration techniques (mean-variance, k-means, nearest neighbor, outlier detection, etc.).
• Strong understanding of

  machine learning pipeline design

  , from data ingestion to model evaluation and deployment.
• Experience with

  deep learning frameworks

  for solving applied problems (e.g., CNNs, RNNs, Transformers).
• Experience working with

  NLP.

• Exposure to

  AI/ML deployment

  on cloud platforms such as

  Azure

  or

  AWS

  .
• Working knowledge of

  Docker

  ,

  CI/CD pipelines

  , and API development (Flask/Django).
• Experience developing

  dashboards or reports

  in Power BI or similar tools.
• Experience mentoring and providing technical direction to team members.

Nice to Have

• Experience with

  LLM-based and GenAI solutions

  , including:

  • RAG

    ,

    Agentic RAG

    ,

    Graph RAG

    ,

    Chain/Tree of Thoughts

    ,

    LangChain

    ,

    content extraction/summarization

    , and

    chat applications

    .
• Applied experience in

  Computer Vision

  (object detection, defect detection, OCR, etc.).
• Domain expertise in one or more of:

  • Supply Chain Analytics

    - inventory optimization, demand forecasting.

  • Sales Analytics

    - recommendation systems, customer segmentation, price elasticity.

  • Manufacturing Analytics

    - root cause analysis, scrap reduction, cycle time reduction, warranty analytics.

Soft Skills

• Excellent

  communication and storytelling

  skills - able to translate data insights into clear, business-focused narratives.
• Strong

  stakeholder management

  and collaboration abilities across diverse teams.
• Ability to

  work independently

  on complex projects while guiding and developing others.