Amazon Pay Data and Analytics team is looking for an experienced Senior Applied 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
- Drive and lead strategic initiatives to employ the most recent advances in ML/AI in a fast-paced, experimental environment
- Build AI/ML models to generate actionable insights for the business
- Create tools and solve challenges using 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
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Experience in building machine learning models for business application
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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