As a Senior Data Scientist, you will lead the development and implementation of Artificial Intelligence and Machine Learning solutions for the Intelligent Industry vertical of Capgemini Invent. You will work closely with product owners, system architects, and client stakeholders to design, develop, and deploy ML/NLP models that meet business requirements, while ensuring compliance with security and privacy standards.
Responsibilities
- Lead the design, development, and implementation of ML/NLP models for various business use cases.
- Analyze and preprocess data, ensuring quality and security compliance.
- Collaborate with stakeholders to understand requirements and deliver scalable solutions.
- Drive ML asset creation and contribute to knowledge sharing within the team.
- Oversee deployment of models using ML pipelines and advanced MLOps practices on cloud or on-premises environments.
- Stay updated with industry trends and propose innovative AI/ML solutions, including Generative AI and LLM-based applications.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or related field.
- 6 to 12 years of related experience as Data Scientist.
- Hands-on experience in Python (NumPy, Pandas, Matplotlib, Seaborn) and SQL.
- Knowledge of data visualization and reporting tools (Tableau, Power BI).
- Strong analytical and problem-solving skills.
- Programming Languages: Python (NumPy, Pandas, Matplotlib, Seaborn), SQL.
- Databases: RDBMS (MySQL, Oracle), NoSQL (MongoDB, Cassandra).
- ML/DL Frameworks: Scikit-learn, TensorFlow, PyTorch.
- Big Data Frameworks: Spark (Spark-ML), H2O.
- Cloud Platforms: Azure/AWS/GCP.
- Predictive modeling using regression, classification, and ensemble methods.
- Advanced experience with deep learning (CNN, RNN, LSTM) and NLP techniques (sentiment analysis, text classification, entity recognition).
- Familiarity with clustering, dimensionality reduction, and recommendation systems.
- Strong understanding of model deployment and MLOps concepts.
- Hands-on experience with Generative AI concepts and building LLM-based applications.
- Understanding of RAG pipelines and vector databases.
Nice to have
- Exposure to OCR, speech recognition, or computer vision.
- Familiarity with OpenAI GPT, LLaMA, or similar models; experience with LangChain or similar frameworks for RAG.
Zobhira
