Senior Data Scientist

About the Role

We seek an experienced Senior Data Scientist with deep expertise in machine learning, predictive analytics, and generative AI to create and maintain AI/ML solutions tailored for the banking and financial services sectors. The successful candidate will demonstrate proficiency in production-level model development within regulated contexts, emphasizing model governance, transparency, and operations.

Primary Responsibilities

• Design, construct, validate, and deploy advanced machine learning and predictive analytics models.
• Conduct extensive exploratory data analyses, perform feature engineering, and enhance model performance.
• Implement explainable AI methods using tools like SHAP and LIME alongside governance frameworks.
• Build and oversee machine learning pipelines leveraging platforms such as MLflow, Databricks, Kubeflow, or AWS SageMaker.
• Work closely with data engineering teams to enable model deployment, continuous monitoring, and drift detection.
• Develop generative AI and large language model (LLM) applications using Retrieval-Augmented Generation (RAG) frameworks targeted at automated document processing.
• Prepare documentation compliant with audit requirements and assist with model risk management and regulatory adherence.
• Communicate analytical insights and model results effectively to business stakeholders and leadership groups.
• Guide and mentor junior data scientists, ensuring adherence to best coding standards and rigorous experimentation protocols.

Required Qualifications & Skills

• Over 7 years in data science with a minimum of 3 years focused on deploying machine learning models in production environments.
• Proficiency in Python programming, utilizing libraries such as Scikit-learn, TensorFlow, PyTorch, and XGBoost; strong alternative experience in R is also considered.
• Solid grounding in statistical methodologies, including hypothesis testing, Bayesian inference, regression techniques, and time series analytics.
• Familiarity with MLOps platforms like MLflow, Databricks, Kubeflow, or SageMaker.
• Hands-on expertise in model explanation approaches (SHAP, LIME) and governance practices.
• Experience developing generative AI solutions, working with LLMs, prompt engineering, and RAG models.
• Exceptional communication skills and ability to manage relationships with business stakeholders.

Preferred Industry Experience

• Background in banking, financial services, or fintech domains.
• Knowledge of credit risk modeling, fraud detection, anti-money laundering (AML) processes, forecasting, and predictive analytics.
• Exposure to model risk management practices.

Additional Information

This role is based in Noida, India and working onsite is expected.

Educational Eligibility: Open to any graduates.

Salary Range: INR 1,000,000 to INR 2,000,000 per annum.