Senior Data Scientist, Amazon Pay

- 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
- 4+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team

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Amazon Pay Data and Analytics team is looking for an experienced Senior Data Scientist with excellent ML/science technical skills. If you are a self-starter, someone who thrives in a fast-paced environment, with a passion for building scalable long-term solutions, then you are the right candidate for our team. In this role, the candidate would work closely with tech teams and product/program across US, EU and JP to build scalable ML/science models. You will be responsible for driving innovation across a wide range of science initiatives, from natural language processing and conversational AI to econometric modeling and ROI-based optimization.

The position is based in Bangalore. We are looking for someone who can familiarize themselves with a dynamic environment, build relationships with cross-functional teams, and assume ownership for a broad array of domains. Our team achieves results through collaboration and clear goals.



Key job responsibilities
- Design and lead large projects and experiments from beginning to end, and drive solutions to complex or ambiguous problems
- Build statistical and AI/ML models to generate actionable insights for the business
- Create tools and solve challenges using statistical modeling, machine learning, optimization, and/or other approaches for quantifiable impact on the business
- Use broad expertise to recommend the right strategies, methodologies, and best practices, teaching and mentoring others
- Key influencer of your team’s business strategy and of related teams’ strategies
- Communication and documentation of methodologies, insights, and recommendations for senior leaders with various levels of technical knowledge