Lead Data Science

Capgemini Invent

Capgemini Invent is the digital innovation, consulting and transformation brand of the Capgemini Group, a global business line that combines market leading expertise in strategy, technology, data science and creative design, to help CxOs envision and build what’s next for their businesses.

Your role

• Predictive and Prescriptive modelling using Statistical and Machine Learning algorithms including but not limited to Time Series, Regression, Trees, Ensembles, Neural-Nets (Deep & Shallow – CNN, LSTM, Transformers etc.). Experience with open-source OCR engines like Tesseract, Speech recognition, Computer Vision, face recognition, emotion detection etc. is a plus.
• Unsupervised learning – Market Basket Analysis, Collaborative Filtering, Dimensionality Reduction, good understanding of common matrix decomposition approaches like SVD. Various Clustering approaches – Hierarchical, Centroid-based, Density-based, Distribution-based, Graph-based clustering like Spectral.
• NLP – Information Extraction, Similarity Matching, Sentiment Analysis, Text Clustering, Semantic Analysis, Document Summarization, Context Mapping/Understanding, Intent Classification, Word Embeddings, Vector Space Models, experience with libraries like NLTK, Spacy, Stanford Core-NLP is a plus. Usage of Transformers for NLP and experience with LLMs like (ChatGPT, Llama) and usage of RAGs (vector stores like LangChain & LangGraps), building Agentic AI applications.
• Graph Analytics – Familiarity with Graph Algorithms (Directed & Undirected) – Traversal (BFS, DFS), Cycle Detection (Bellman Ford, Flyod Warshall), Shortest Path (Dijkstra, A*) etc. Building Knowledge Graphs with unstructured data and knowledge graph optimizations like PageRank/TrustRank is expected
• Mathematical Optimization – Familiarity with common optimization algorithms, both discrete– Linear, Mixed-Integer, Goal, Dynamic etc and continuous – GD and its variants, Newton’s method etc. is expected. Experience with Simulated Annealing and exposure to ML inspired evolutionary optimization algorithms like Genetic Algorithm & Genetic Programming for optimization is a plus.
• Simulations – Monte Carlo Simulation, Discrete-Event Simulation, Agent-Based Simulation, Hybrid Simulation, System Dynamics, Genetic Algorithm based Simulation.
• Model Deployment – ML pipeline formation, data security and scrutiny check and ML-Ops for productionizing a built model on-premises and on cloud.

Your Profile

• Programming Languages – Python – NumPy, SciPy, Pandas, MatPlotLib, Seaborne
• Databases – RDBMS (MySQL, Oracle etc.), NoSQL Stores (HBase, Cassandra etc.)
• ML/DL Frameworks – SciKitLearn, TensorFlow (Keras), PyTorch,
• Big data ML Frameworks - Spark (Spark-ML, Graph-X), H2O
• Cloud – Azure/AWS/GCP
• 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
• Experience working in a consulting environment is highly desirable.

What you will love about working here

• We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance.
• At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities.
• Equip yourself with valuable certifications in the latest technologies such as Generative AI.

About Capgemini

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of €22.5 billion.