Data Scientist II, WW Installments

Come build the future of FinTech!

The WW Installments team within Consumer Payments (CP) brings together the best of analytics, machine learning, tech, business, and finance to deliver for customers across the world. We build the foundational systems and products to enable Amazon customers with installment and related payment methods across the globe. Our mission is to delight our customers by building payment experiences and financial services that are trusted, valued and easy to use from anywhere in any way. Our products are growing rapidly and we are continuously adding new market-leading features and launching new customer facing ML solutions. Our team of high caliber engineers, scientists, developers and product managers use rigorous quantitative approaches to ensure that we target the right product to the right customer at the right moment, managing tradeoffs between competitiveness, click through rate, approval rates, customer friction, economic profit, and loss rates. We leverage the wealth of Amazon’s information to build a wide range of probabilistic models, set up experiments that ensure that we are thriving to reach global optimums and leverage Amazon’s technological infrastructure to display the right offerings in real time. Our goal is to delight our customers with their purchasing experience and our solutions improve the shopping experience for hundreds of millions of consumers worldwide accordingly. Those of us who love to work with data see this as the pinnacle of opportunities within FinTech and the BNPL/Installment space that you cannot find anywhere else in the world.

As a Data Scientist within WW Installments, you will be responsible for building machine learning models and solutions with direct customer impact. These models represent a core capability for WW Installments and businesses across Amazon. Your work will directly impact customers by influencing how they interact with financing options to make purchases. You will work across functions including business intelligence, data engineering, software development, and business to induce data driven decisions at every level of the organization.

The right candidate will possess excellent business and communication skills, transform ambiguous business problems to an analytical problem and prioritize work across the team to support business outcomes, and develop solutions to key business questions.

Key job responsibilities
This role will be responsible for:
• Developing machine learning models and analytical solutions for the global Installments Competitive Pricing team
• Apply expertise in machine learning to develop large-scale systems that are deployed across Amazon businesses.
• Identify business opportunities, define and execute modeling approach, then deliver outcomes to various Amazon businesses with an Amazon-wide perspective for solutions.
• Lead the project plan from a scientific perspective on product launches including identifying potential risks, key milestones, and paths to mitigate risks.
• Own key inputs to reports consumed by VPs and Directors across Amazon.
• Identifying new opportunities to influence business strategy and product vision using data science and machine learning.
• Continually improve the WW Installments ML roadmap automating and simplifying whenever possible.
• Coordinate support across engineers, scientists, and stakeholders to deliver ML pipelines, analytics projects, and build proof of concept applications.
• Work through significant business and technical ambiguity delivering on analytics roadmap across the team with autonomy.

BASIC QUALIFICATIONS

- 3+ years of relevant professional experience working with data and applied analytics.
- MS in data science, applied mathematics, economics, operational research, statistics, engineering or a related technical discipline.
- Experience with at least one statistical programming language such as Python, Julia, or R.
- Proficiency in model development, model validation and model implementation for large-scale applications.
- Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
- Ability to convey mathematical results to non-science stakeholders.
- Excellent communication (verbal/written) and data presentation skills and demonstrated ability to successfully partner with business and technical teams.
- Experience building data products incrementally and integrating and managing datasets from multiple sources
- Ability to deal with ambiguity and competing objectives in a fast-paced environment.

PREFERRED QUALIFICATIONS

- PhD in data science, applied mathematics, economics, operational research, statistics, engineering or a related technical discipline.
- 5+ years of industry experience applying machine learning models in a business context.
- Expertise on a broad set of ML approaches and techniques including ensemble learning, deep learning, and non-parametric methods.
- Ability to work effectively within an interdisciplinary team of Data Scientists, Economists, BIEs, Data Engineers, and Product Managers.
- Experience with AWS, cloud computing.
- Ability to develop analytics plans for data modeling processes.
- Experience in payment products, recommendation engines, and risk modeling.
- Significant peer reviewed scientific contributions in relevant field.