Role & responsibilities

We are seeking a seasoned Data Scientist to join our dynamic Data Science & Analytics team in Mumbai. In this role, you will lead the end-to-end development and deployment of data-driven solutions, from problem definition to production monitoring. You will leverage your strong foundation in statistics, machine learning, and Generative AI to drive significant business impact and mentor junior team members. This is an opportunity to work on complex, real-world problems in a fast-paced, collaborative environment.

• End-to-End Project Leadership: Take ownership of data science projects, from initial research and experimentation to scalable deployment, monitoring, and ongoing optimization.

• Model Development: Design, build, and optimize advanced statistical and machine learning models to solve complex business problems.

• LLM & Generative AI: Research and implement innovative LLM/GenAI solutions, including advanced prompt engineering, Retrieval-Augmented Generation (RAG) frameworks, and parameter-efficient fine-tuning for specific business needs.

• Cross-functional Collaboration: Partner with product, engineering, and business stakeholders to translate complex challenges into actionable data science solutions and communicate findings effectively to technical and non-technical audiences.

• Infrastructure & Deployment: Work with data engineering teams to design scalable data models and robust, automated ML pipelines using MLOps best practices and cloud services (AWS/GCP/Azure).
• Performance Monitoring: Implement monitoring frameworks to track and enhance the performance of deployed models.

Preferred candidate profile

• Machine Learning & Statistics:

• Strong foundation in supervised & unsupervised ML algorithms, evaluation metrics, and feature engineering.
• Practical experience with hands-on modelling and experimentation.

• LLM & Generative AI:

• Conceptual and practical understanding of LLM architecture, prompt engineering, RAG, parameter fine-tuning, and LLM evaluation/monitoring.
• Exposure to vector databases
• Executed at least 1 impactful LLM/GenAI implementation in real-world settings.

• Programming:

• Proficiency in Python, R, and SQL for model development and data analytics.

• Deployment & Automation:

• Experience with cloud platforms (AWS/GCP/Azure)
• API integration and orchestration for scalable solutions.

Practical experience with MLOps tools like MLflow, Docker, or Kubernetes for CI/CD pipelines.