Data Scientist

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

1. 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.

2. 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.

3. 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.

4. 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.

5. 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

6. 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.

7. 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