Data Scientist II, JWO

*This position is located in Bengaluru

As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.

With Just Walk Out (JWO), our mission is to build the future of physical retail in collaboration with Amazon Go and Fresh Stores, in addition to stadiums, airports, healthcare facilities and university campuses looking to increase throughput, extend operating hours and improve efficiency. In addition we have conviction that visual understanding and reasoning can be applied in multiple new ways to manage physical spaces.


The Role

In this role, you will apply advanced analysis technique and statistical concepts to draw insights from massive datasets, create intuitive data visualizations, and build scalable machine learning models. You are a pragmatic generalist. You can contribute to each layers of a data solution – you work closely with business intelligence engineers, data engineers and product managers to obtain relevant datasets and prototype predictive analytic models, you team up with data engineers and software development engineers to implement data pipeline to productionize your models, and review key results with business leaders and stakeholders. Your work exhibits a balance between scientific validity and business practicality.

To be successful in this role, you must be able to turn ambiguous business questions into clearly defined problems, develop quantifiable metrics and robust machine learning models from imperfect data sources, and deliver results that meet high standards of data quality, security, and privacy.


1. Define and conduct experiments to optimize JWO shopping experience and inquires, and communicate insights and recommendations to product, engineering, and business teams
2. Interview stakeholders to gather business requirements and translate them into concrete requirement for data science projects
3. Build models that forecast growth and incorporate inputs from product, engineering, finance and marketing partners
4. Define metrics and design algorithms to estimate customer satisfaction and engagement in real-time
5. Apply data science techniques to automatically identify trends, patterns, and frictions of customer interaction and retention
6. Work with data engineers and software development engineers to deploy models and experiments to production
7. Identify and recommend opportunities to automate systems, tools, and processes.


Key job responsibilities
1. Build and maintain time series forecasting models for demand planning using advanced forecasting tools and Python.
2. Design and build simulators and automated processes for shift planning and other organizational needs.
3. Define and evaluate key business metrics to drive decision-making and strategy.
4. Develop machine learning tools to enhance operational efficiency and human-in-the-loop processes.
5. Conduct anomaly detection and predictive analysis to forecast hardware failures and maintain operational continuity.
6. Leverage sampling methods and uncertainty analysis to evaluate associate performance accurately and cost-effectively.
7. Conduct experiments, including A/B tests, to support business decisions and model development.
8. Stay up to date with developments in generative AI, incorporating latest techniques into tools and models.
9. Develop statistical models to evaluate current systems and identify optimization opportunities.
10. Work autonomously and manage projects with little oversight, driving them from inception to implementation.
11. Regularly write up your work and findings in internal doc reviews

About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- 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

- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company

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.

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