Sr. Data Scientist - Marketing & Customer Analytics

Job Summary

Please find the JD for Sr. Data Scientist. (Gen AI/ML)

Location: Gurgaon

We are looking for a highly skilled ML & AI candidate to drive Marketing and cross-sell initiatives. The role will focus on building scalable ML & AI solutions, integrating GenAI capabilities, and deploying models into production to enable data-driven decision-making across customer lifecycle, risk management and business expansion initiatives.

Responsibilities

• Data Analysis and Modelling: Apply statistical, ML & AI techniques to analyse complex datasets, identify patterns, and develop predictive models to solve business problems.
• Data Exploration and Preparation: Collect, cleanse, and pre-process data from various sources to ensure its accuracy, completeness, and quality.
• Feature Engineering: Identify and engineer relevant features from structured and unstructured data sources (behavioral, transactional, and alternative data signals) to enhance exiting model predictability.
• ML Model Development: Design and develop innovative AI and ML models. Evaluate model performance using appropriate metrics and fine-tune models for optimal results.
• AI/GENAI Implementation: Develop and implement GenAI use cases such as chatbots, document processing etc. Work with large language models (LLMs) for banking-specific applications along with fine-tune and optimize GenAI models (SLM Models) for domain-specific accuracy and performance.
• Model Deployment & MLOps: Deploy models into production using cloud platforms. Build and manage end-to-end ML pipelines ensuring proper model governance, explainability.
• Communication: Communicate complex analytical concepts and findings to both technical and non-technical stakeholders.

Education

Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field

Experience

3+ years of hands-on experience as a Data Scientist/Engineer- ML & AI

Skills & Competencies

• Candidate must demonstrate proficiency in programming languages including Python (Pandas, Numpy, TensorFlow, PyTorch, Scikit-learn), Py-Spark, and SQL.
• Experience in utilizing Big Data platforms such as Databricks, Azure, or AWS is required.
• Experience working with LLMs (OpenAI, open-source models like LLMA, etc.) is essential.
• Knowledge of Prompt engineering, Embeddings & vector databases & RAG architecture, with exposure to NLP, deep learning, and AI-driven automation use cases.
• Experience in AI productization and API-based model deployment
• A background in the Insurance, Banking, or NBFC sectors is preferred.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.