Lead Data Scientist
Confirmed on the employer's own hiring board on Oct 4, 2026. First seen by Alion on Jul 28, 2026. Capgemini scores A on the Alion truth index.
At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities, collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client's challenges of today and tomorrow. Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose.
Your Role
- Programming Languages- Python - NumPy, SciPy, Pandas, MatPlotLib, SeaborneDatabases- 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.
- Predictive and Prescriptive modellingusing 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.
Your Profile
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.
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.
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, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.