Apache Hadoop, C++, JavaScript, MxNet, NumPy, Python Programming, Scikit-learn, SciPy, TensorFlow
F2 & XCAT Tech Discovery Science is looking for a Senior Applied Scientist to lead our ML visioning, roadmap planning, as well as building Machine Learning solutions to solve economic problems at scale. Discovery uses Machine Learning, Deep Learning, Reinforcement Learning, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business. We also develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are a science-driven team incubating and building disruptive solutions using cutting-edge technology to solve some of the toughest business problems at Amazon.
You will work with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed ML models and services. You will partner with scientists, product managers, and engineers to help invent and implement scalable ML, RL, and econometric models while building tools to help our customers gain and apply insights. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale economic problems, enable measurable actions on the Consumer economy, and work closely with scientists and economists. We are particularly interested in candidates with experience building predictive models and working with distributed systems.
As a Sr. Applied Scientist, you bring structure to ambiguous business problems and use science, logic, and practical experience to decompose them into straightforward, scalable solutions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems; you're interested in learning; and you acquire skills and expertise as needed.
About the team
The mission of our team is to make Amazon’s online store the preferred shopping destination for customers by creating discovery and evaluation experiences that delight. We enable customers to discover products they love by using data, computer vision, and machine learning to organize, rank, blend with ads, and create browsable and personalized recommendations.
We are open to hiring candidates to work out of one of the following locations:
San Diego, CA, USA | Seattle, WA, USA | Sunnyvale, CA, USA
BASIC QUALIFICATIONS
PREFERRED QUALIFICATIONS
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Amazon.com, Inc. is an American multinational technology company with operations in cloud computing, streaming media, artificial intelligence, and e-commerce. The company has been referred to as one of the most influential economic and cultural forces in the world, and it is one of the world's most valuable brands.
Vancouver, BC, Canada
2-4 year
Toronto, ON, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
Toronto, ON, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
Berlin, Germany
2-4 year
Rome, Metropolitan City of Rome, Italy
2-4 year
Arlington, VA, USA
2-4 year
Austin, TX, USA
2-4 year
Bellevue, WA, USA
2-4 year
California City, CA, USA
2-4 year
Newark, NJ, USA
2-4 year
Newark, NJ, USA
2-4 year
Palo Alto, CA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Sumner, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Mumbai, Maharashtra, India
2-4 year
Berlin, Germany
2-4 year
New York, NY, USA
2-4 year
New York, NY, USA
2-4 year
New York, NY, USA
2-4 year
New York, NY, USA
2-4 year
New York, NY, USA
2-4 year
Westborough, MA, USA
0-2 year
Arlington, TX, USA
2-4 year
Seattle, WA, USA
6-8 year
Sunnyvale, CA, USA
6-8 year
New York, NY, USA
6-8 year
Seattle, WA, USA
4-6 year
North Reading, MA, USA
4-6 year
Palo Alto, CA, USA
0-2 year
New York, NY, USA
0-2 year
Seattle, WA, USA
0-2 year
Arlington, VA, USA
0-2 year
New York, NY, USA
4-6 year
Arlington, VA, USA
4-6 year
Seattle, WA, USA
4-6 year
San Diego, CA, USA
4-6 year
Irvine, CA, USA
4-6 year
San Francisco, CA, USA
4-6 year
Brisbane QLD, Australia
0-2 year
Adelaide SA, Australia
0-2 year
Canberra ACT, Australia
0-2 year
Toronto, ON, Canada
0-2 year
Vancouver, BC, Canada
4-6 year
Vancouver, BC, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
San José Province, San José, Costa Rica
0-2 year
Palo Alto, CA, USA
0-2 year
Seattle, WA, USA
0-2 year