Sr. Applied Scientist, Private Brands Intelligence - SCIT Science

Amazon • Vancouver, BC

2d • CA$195,900 - CA$327,200 • Onsite

About The Position

The Private Brands team is looking for a Sr. Applied Scientist to join the team in building science solutions at scale. Our team applies Optimization, Machine Learning, Statistics, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business and develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Scientists, Engineers, and Economists. You will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable optimization solutions and ML models. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and economists. As a Sr Scientist, you bring business and industry context to science and technology decisions. 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, acquiring expertise as needed. You decompose complex problems into straightforward solutions. We are particularly interested in candidates with experience in Operations Research and predictive models and working with distributed systems. Academic and/or practical background in Operations Research, Machine Learning and Reinforcement Learning are particularly relevant for this position.

Requirements

• 3+ years of building machine learning models or developing algorithms for business application experience
• PhD, or Master's degree and 5+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with conducting research in a corporate setting

Nice To Haves

• 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.
• Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices
• Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences
• Experience in Operations Research and predictive models
• Experience working with distributed systems
• Academic and/or practical background in Operations Research, Machine Learning and Reinforcement Learning

Responsibilities

• Translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable optimization solutions and ML models.
• Bring business and industry context to science and technology decisions.
• Set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms.
• Tackle intrinsically hard problems, acquiring expertise as needed.
• Decompose complex problems into straightforward solutions.

Benefits

• health insurance (medical, dental, vision, prescription, basic life & AD&D insurance)
• Registered Retirement Savings Plan (RRSP)
• Deferred Profit Sharing Plan (DPSP)
• paid time off
• other resources to improve health and well-being

What This Job Offers

• Job Type: Full-time
• Career Level: Senior