Lead Data Scientist - Manufacturing & Process Analytics

The Sr Data Scientist will develop and implement Artificial Intelligence based solutions across various disciplines in Capgemini. In this role, the candidate will contribute to the development and deployment of modern machine learning, artificial intelligence, statistical methods, operations research, semantic analysis etc. for finding structure in large data sets. The candidate will be responsible for executing data science projects independently to deliver business outcomes and is expected to demonstrate domain expertise, develop, and execute program plans and proactively solicit feedback from stakeholders to identify improvement actions. This role requires a strong technical background, excellent problem-solving skills, and the ability to work collaboratively with stakeholders from different functional and business teams.

Required Qualifications:

Bachelors degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.

At least 4 years of experience in Information Technology

Good experience in programming languages such as Python/Java/Scala, SQL and experience with data visualization tools like Tableau or Power BI etc.

At least 3 years of experience in Cloud platforms (e.g., ADF, Data bricks, Azure) and their AI services.

At least 6-8 years of experience in data science & 1 year with a focus on supply chain analytics, supply chain processes, including demand forecasting, inventory optimization, logistics, and procurement.

Conduct in-depth analysis of customer behaviour and preferences to inform feature engineering and model architecture decisions

• At least 5+ years of experience in Python/ Pyspark with hands on delivery experience; Pandas/ NumPy, TensorFlow, Flask/ FastAPI, scikit-learn
• Back-end query and any cloud like Azure, AWS and GCP exp.
• Gen AI and Agentic AI depth knowledge.

Preferred Qualifications:

Experience with machine learning frameworks, optimization solvers, and big data ecosystems (e.g., Hadoop, Spark).

Advanced degree (Master’s or Ph.D.) in Data Science, Manufacturing Management and process , Operations Research, Industrial Engineering, or a related field

Experience in price sensitivity analysis, cost-plus pricing, value-based pricing, promotional effectiveness analysis, and tiered pricing strategies.

Experienced in Agile way of working, manage team effort and track through JIRA

Experience in Proposal, RFP, RFQ and pitch creations and delivery to the big forum .

Experience in POC, MVP , PoV and assets creations with innovative use cases

High Impact client communication

Experience working in a consulting environment is highly desirable.

The job may also entail sitting as well as working at a computer for extended periods of time. Candidates should be able to effectively communicate by telephone, email, and face to face.