Senior Decision Scientist, Decision Sciences

Amazon Inc.; Pune District; Hybrid; INR 4,000,000 - 6,000,000; Full time

Job summary

Amazon Inc. in Pune, India is seeking a Senior Decision Scientist to design, build, and deploy ML models for credit risk, income estimation, fraud detection, and portfolio optimization.

You will leverage credit bureau and transaction data, guiding lending decisions and customer outcomes. You will work with risk, product and collections teams to define challenges, deploy scalable data pipelines, and ensure governance and regulatory compliance.

Qualifications

• 5+ years of data scientist experience.
• 5+ years of experience with SQL and Python or R/SAS.
• Master’s degree in STEM or equivalent experience in STEM fields.
• Experience applying theoretical models in real-world environments.
• Knowledge of ML concepts and their applications to reasoning and problem-solving.

Responsibilities

• Understand lending business, data, regulatory context and data science practices.
• Collaborate with risk, product and collections teams to address business challenges.
• Design and implement ML solutions for credit risk scoring, income prediction, fraud detection, and portfolio optimization.
• Develop model validation, monitoring and governance compliant with regulations.
• Deploy ML solutions into production with low latency and scalable data pipelines.
• Mentor junior team members and present findings to senior leadership.

Skills

Data science

Machine learning

SQL

Python

R

Education

Master's degree in STEM

Tools

AWS (S3)

Redshift

Sagemaker

EMR

Kinesis

Lambda

EC2

Hadoop

Spark

MapReduce

Hive

Job description

Senior Decision Scientist, Decision Sciences

We are seeking a talented and motivated Data Scientist to join our 1P Lending team. In this role, you will design, build, and deploy machine learning models and analytical frameworks that drive credit risk assessment, income estimation, fraud detection, and portfolio optimization. You will work with credit bureau data, transactional data, and alternative behavioral signals to create models that directly impact lending decisions and customer outcomes.

Key job responsibilities

• Understand lending business, products, data consumed to make decisions, regulatory context, and practice of Data Science related to this field.
• Closely Interact with risk, product and collection team to understand the business challenges.
• Define, Design and Implement complex ML solutions for various credit lifecycle stages like credit risk scoring, income prediction, collection optimisation, sales optimisation, fraud detection etc.
• Create robust model validation, monitoring, and governance solutions in compliance with regulatory requirements.
• Help the Decision-Engine team to deploy the ML solutions in production with sub-second latency.
• Develop new modeling techniques and analytical frameworks for innovative lending products within the regulatory landscape.
• Drive end-to-end delivery of scalable data pipelines from ideation to production deployment.
• Optimize performance and accuracy of existing ML solutions.
• Derive actionable insights from massive and diverse datasets.
• Lead analytical design and implementation for new global market geographies.
• Mentor junior team members in data science best practices.
• Present findings and recommendations to senior leadership with clear, data-backed conclusions.

About the team

As Decision Sciences team supporting 1p lending, we use Data Science, Machine Learning, and advanced analytics on massive datasets to power credit decisioning, risk management, and customer experience optimization.

We operate at the intersection of ML, Fintech and E-commerce, working on cloud scale ML infrastructure. If explainable GenAI, Probabilistic Graph Models, DNNs and Monte Carlo Simulations excite you, then we are the right team for you.

Basic Qualifications

• 5+ years of data scientist experience
• 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
• Experience applying theoretical models in an applied environment
• Knowledge of machine learning concepts and their application to reasoning and problem-solving

Preferred Qualifications

• Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
• Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
• Experience applying quantitative analysis to solve business problems and making data-driven business decisions
• Experience working on multi-team, cross-disciplinary projects
• Experience in defining and creating benchmarks for assessing GenAI model performance
• Experience effectively communicating complex concepts through written and verbal communication

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.