Senior Data Scientist

Job Title : Senior Data Scientist

Experience: 5 to 12 Years

Work Mode: Hybrid

Location : Pune

Notice Period: Immediate joiners preferred ( 0 to 30 days) We are looking for a highly skilled Senior Data Scientist with strong expertise in Machine Learning, Machine Learning Services, Recommender Systems, and Generative AI (LLM/LVM). The ideal candidate will have hands-on experience building end-to-end ML solutions, from data exploration and model development to deployment, monitoring, and production support. You will work closely with Data Engineering, Data Science, and ML Engineering teams to design, develop, deploy, and scale intelligent data products and enterprise AI solutions.

Key Responsibilities Data Science & Advanced Analytics

• Develop and deploy end-to-end Machine Learning models from ideation to production.
• Perform EDA, feature engineering, model training, and evaluation.
• Build predictive and prescriptive models using statistical and machine learning techniques.
• Optimize models for accuracy, performance, scalability, and reliability. Machine Learning Services – Primary Focus
• Design and implement scalable ML pipelines for training, testing, deployment, and monitoring.
• Work with cloud ML platforms such as Azure ML, AWS SageMaker, and GCP Vertex AI.
• Implement model lifecycle management, including versioning, monitoring, retraining, and governance.
• Support production ML deployments and continuous model improvement. Recommender Systems
• Design and develop recommendation engines using:
• Collaborative filtering
• Content-based recommendations
• Hybrid recommendation systems
• Develop ranking and personalization algorithms.
• Work with large-scale datasets for user segmentation and personalization.
• Evaluate recommendation models using Precision@K, Recall@K, and NDCG. Generative AI – LLM & LVM
• Build and deploy LLM-powered applications, including chatbots, copilots, and document intelligence solutions.
• Design and implement RAG (Retrieval-Augmented Generation) architectures.
• Work with models and platforms such as OpenAI, Azure OpenAI, Hugging Face, GPT, and Llama.
• Develop solutions for text generation, summarization, classification, and multimodal/image/video understanding.
• Implement prompt engineering and prompt optimization workflows. Data Engineering Collaboration
• Define data requirements and collaborate with Data Engineering teams on pipeline design.
• Ensure data quality, governance, and availability.
• Work with Spark, Databricks, and Hadoop for large-scale data processing. ML Engineering & Deployment
• Deploy ML models through APIs and microservices.
• Containerize applications using Docker and Kubernetes.
• Integrate ML solutions into CI/CD pipelines and production systems.
• Support scalable and reliable ML application deployments. Model Monitoring & Responsible AI
• Monitor model drift, performance degradation, and bias.
• Implement logging, alerting, explainability, and monitoring mechanisms.
• Ensure adherence to Responsible AI principles, including fairness, transparency, and interpretability.

Required Qualifications

• 5–8 years of experience in Data Science, Machine Learning, AI, or a related field.
• Strong hands-on experience with Python and SQL.
• Proven experience in end-to-end ML model development, deployment, and production support.
• Strong understanding of supervised and unsupervised learning, predictive modeling, and model optimization.
• Experience with at least one cloud ML platform:
• Azure ML
• AWS SageMaker
• Google Vertex AI
• Hands-on experience developing Generative AI solutions using LLMs, RAG, and prompt engineering.
• Experience working with Data Engineering and ML Engineering teams.
• Experience delivering enterprise-scale AI solutions in an Agile environment.