Amazon.com Services LLC
Applied Science, global corporate
Sr.AppliedScientist,PXTCentralScience
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“Sr. Applied Scientist, PXT Central Science at Amazon.com Services LLC. Skills: Causal inference, Machine learning, Predictive modeling. Design causal predictive models. Develop systems that forecast workforce outcomes”
What You'll Achieve.
Develop models that empower data-driven workforce decisions; Develop models that shape how Amazon supports its workforce
Industry & Context.
Transform complex operational challenges into actionable insights
What They're Looking For.
Must Have
PhD or Master's degree and 6+ years of applied research experience, 5+ years of building machine learning models for business application experience, Experience programming in Java, C++, Python or related language, Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Nice to Have
PhD in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field, Experience with neural deep learning methods and machine learning, Experience in causal modeling like graphical models, causal Bayesian network, potential outcomes, A testing, experiments, quasi-experiments, and data science workflows, Experience in taking a product from conception & definition phase through engineering design and taking it to market, Experience working with emerging technologies, Experience in mentoring, leading and coaching
What You'll Do.
Design causal predictive models
Develop systems that forecast workforce outcomes
Identify actionable drivers behind workforce outcomes
Enable leaders to intervene before problems materialize
Pioneer novel feature engineering
Bring creative approaches from LLMs into causal modeling
Unlock signal that traditional methods miss
Write production-quality science code
Implement code into operational decision-making tools
Bridge disciplines by translating between economists
Synthesize causal rigor with ML innovation
Produce scientifically defensible and operationally useful models
Design and execute experiments to validate causal claims
Design and execute experiments to validate model performance
Establish evaluation standards
Develop and elevate peers across the team
Mentor scientists in adjacent disciplines
Share technical knowledge
Raise collective bar on modeling and engineering practices
Present findings to senior leadership
Distill complex causal and predictive insights into clear
How You'll Work.
Team & Collaboration
Cross-functional teams; Partner engineering teams; Work with economists; Work with data scientists; Work with engineers
Communication Scope
Present findings; Clear recommendations
Full Job Description
Every day, hundreds of thousands of Amazon associates show up to fulfill the promise we make to our customers. Behind the workforce decisions that support them — staffing, retention, scheduling, development — there should be science that doesn't just describe what happened, but explains why it happened and predicts what comes next. That's the work we do. PXT Central Science (PXTCS) is Amazon's internal research organization dedicated to bringing scientific rigor to people and workforce decisions at global scale. Our team sits within the part of PXTCS that focuses on Amazon's Tier 1 hourly populations — the associates at the heart of Amazon's operations. We are a multidisciplinary group of 15 economists, data scientists, data engineers, and research scientists united by a single mission: to transform complex operational challenges into actionable insights through rigorous causal analysis and predictive modeling that empowers data-driven workforce decisions. We are building something new — causal predictive models that go beyond traditional forecasting. Our models don't just tell leaders what will happen; they reveal why it will happen and what levers they can pull to change the outcome. This is the frontier where causal inference meets modern machine learning, and we need a scientist who can help us push it forward. As a Senior Applied Scientist on this team, you will be the connective tissue between innovative research and real-world impact. You will work shoulder-to-shoulder with economists who deeply understand the causal mechanisms driving workforce dynamics and data scientists who know the operational landscape — and you will bring the technical creativity to expand what's possible. That means writing production-quality code that our partner engineering teams can implement into decision-making tools. It means exploring novel feature spaces — large language models, computer vision, and other emerging techniques — to unlock signal that traditional approaches miss.
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