Data Scientist II, Amazon Pay

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
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 - 2+ years of data scientist experience
- 3+ years of data querying languages (e. g. SQL), scripting languages (e. g. Python) or statistical/mathematical software (e. g. R, SAS, Matlab, etc. ) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment