Job Title: Data Scientist
(Position 3-Open)
Department: CIBD3
Reports To: Manish Kaurava -SDM Data Science and Analytics
Job Location: IN/PL/SB
Data Scientist – Role Overview
We are seeking a highly skilled
Data Scientist with strong expertise in
Machine Learning services, Recommender Systems (RS), and Generative AI (LLM & LVM). The role will collaborate closely with
Data Engineering, Data Science, and ML Engineering teams to design, develop, deploy, and scale intelligent data products and AI solutions.
Key Responsibilities
- Data Science & Advanced Analytics
- Develop and deploy end-to-end machine learning models from ideation to production.
- Perform exploratory data analysis (EDA), feature engineering, and model evaluation.
- Build predictive and prescriptive models using statistical and ML techniques.
- Machine Learning Services (Primary Focus)
- Design and implement scalable ML pipelines for training, testing, and deployment.
- Work with ML platforms such as:
- Azure ML, AWS SageMaker, GCP Vertex AI
- Implement model lifecycle management including versioning, monitoring, and retraining.
- Optimize models for performance, scalability, and reliability.
- Recommender Systems (RS)
- Design and build personalized recommendation engines:
- Collaborative filtering
- Content-based filtering
- Hybrid recommendation systems
- Work with large-scale datasets to implement ranking, personalization, and user segmentation.
- Evaluate models using metrics like precision@k, recall@k, NDCG.
- Generative AI (GenAI – LLM & LVM)
- Build and deploy LLM-powered solutions:
- Chatbots, copilots, document intelligence
- Implement RAG (Retrieval-Augmented Generation) architectures.
- Work with models such as:
- OpenAI, Azure OpenAI, Hugging Face
- Develop use cases for:
- Text generation, summarization, classification
- Image/video understanding (LVM – Large Vision Models)
- Optimize prompts and manage prompt engineering workflows.
- Collaboration with Data Engineering
- Define data requirements and collaborate on data pipeline design.
- Ensure data quality, governance, and availability.
- Work with big data technologies like:
- Spark, Databricks, Hadoop
- ML Engineering & Deployment Support
- Collaborate with ML Engineers to:
- Deploy models via APIs and microservices
- Containerize models (Docker, Kubernetes)
- Integrate models into production systems and CI/CD pipelines.
- Model Monitoring & Governance
- Monitor model drift, performance degradation, and bias.
- Implement logging, alerting, and explainability tools.
- Ensure Responsible AI practices:
- Fairness, transparency, interpretability
Qualifications & Experience
Educational Background
- B.Tech/B.S./ M.S. in Computer Science, Statistics, Mathematics, or a related field
Professional Experience
- 5+ years of experience in Data Science / Machine Learning roles
- Proven experience in end-to-end ML model development and deployment
Technical Skills
Core Technical Skills
- Programming: Python (mandatory), SQL
- ML Libraries: Scikit-learn, TensorFlow, PyTorch
- Data Processing: Pandas, NumPy, Spark
ML & AI Expertise
- Strong expertise in:
- Supervised & Unsupervised Learning
- Model optimization techniques
- Hands-on experience with ML platforms and services
Recommender Systems
- Experience in designing and deploying recommendation engines
- Knowledge of ranking algorithms and personalization techniques
Generative AI Skills
- Experience with:
- LLMs (GPT, Llama, etc.)
- Prompt engineering
- RAG frameworks (LangChain, LlamaIndex)
- Exposure to multimodal AI (LVM) is a strong plus
MLOps & Deployment
- Familiarity with:
- CI/CD for ML pipelines
- Docker, Kubernetes
- Understanding of model monitoring tools
Data Engineering Understanding
- Strong knowledge of:
- Data pipelines, ETL processes
- Data warehousing concepts
Additional Skills & Preferred Qualifications
- Strong communication, stakeholder management, and organizational skills
- Self-motivated, customer-focused, and detail-oriented mindset
- Experience with Azure ecosystem (Azure ML, Databricks)
- Exposure to real-time data processing
- Certifications in: Machine Learning / AI / Cloud
- Knowledge of ERP systems (SAP) – strongly preferred
- Six Sigma Yellow Belt or Green Belt certification – a plus
- ITIL certification – a plus
