Data Scientist, Experimentation and Causal Inference

Seattle, WA or Remote /
Data Science /
Full Time
At Shelf Engine, our mission is to reduce food waste through automation. We harness the power of AI to provide real-time, intelligent forecasting for food retailers like grocery stores, restaurants, and cafes across the United States. We’re able to drastically reduce the amount of food waste, which in turn drives profit for retailers, lowers costs for consumers, and reduces the negative ecological and social impacts of waste. 

Shelf Engine is searching for talented Data Scientists to own and drive experimentation and causal inference to improve the abilities for Shelf to deliver on its mission. This person will join our growing team and report directly to our Head of Data Science. In this role, you will design, build, and launch scalable, scientifically rigorous measurement, monitoring, and experimentation systems to identify heterogeneous treatment effects, and derive statistically-robust and causal inferences in the face of partially observable, incomplete, censored, endogenous, and diverse data. You’ll apply your expertise and breadth of knowledge in statistics, causal inference, and experimentation to identify appropriate solutions, and to establish scalable, rigorous frameworks using your skills in code and productionalization to prototype, launch, and iterate. You will spearhead experimentation across the organization, working cross-functionally, and leveraging our team of machine learning and forecasting experts, Engineers, Operations, Customer Success, and Field teams to gain critical insights, and create approaches that balance scientific rigor with strategic implementation, speed, and efficiency. If you have a passion for solving complex problems, working collaboratively with an awesome and supportive team, and making a huge social impact, this may be your dream job. 

The goal is to help Shelf Engine develop and productionalize best-in-class AI and machine learning models at-scale to achieve business objectives. Your strengths in statistics, causal inference, and experimentation, alongside your quick adaptability to understand business requirements will directly impact our ability to deliver on our mission; striking a fine balance between reducing customers’ food waste, and avoiding understocking situations given the uncertainties of demand, pricing, promotions, vendor capacity, lead times, inventory, product nuances, and customer experience. Join us to solve critical problems and use your skills in causal inference and experimentation for a positive social impact.

As an Experimentation and Causal Inference Data Scientist at Shelf Engine, you will:

    • Embrace our company principles through inclusive, authentically-kind, and empathetic interactions with our team and our customers 
    • Design, build, and launch scalable, scientifically rigorous measurement, monitoring, and experimentation systems to improve understanding of performance, impact, and attribution in ongoing evaluation on data at scale
    • Own the end-to-end experience including R&D, prototyping and launching scalable, rigorous frameworks, and presenting actionable insights to internal stakeholders - combining statistical expertise, business acumen, communication, and technical skills in code and productionalization
    • Research, build, launch, monitor, and develop sophisticated algorithms and solutions to solve complex problems for a rapidly evolving product
    • Work cross-functionally (e.g. Product, Engineering, Operations, etc) to frame problems scientifically, and to create and run experiments and algorithms enabling statistically-robust and causal inferences that solve complex problems 
    • Continuously improve the quality and accessibility of our data science capabilities and frameworks including modeling, monitoring, experimentation, inference, and reporting  

We think you would make a great Experimentation and Causal Inference Data Scientist if you have:

    • A PhD in a related quantitative field (such as Economics, Political Science, Statistics, Psychology or a related field) along with 3+ years hands-on experience designing and implementing experimentation or causal inference solutions 
    • Expertise in advanced statistical methods, A/B testing, experimental design, causal inference, field experiments, quasi-experimental methods, multi-level / hierarchical modeling, matching, regression discontinuity, interrupted time series, dosage models, Bayesian methods, and machine learning a plus 
    • 2+ years of experience outside of an academic setting building end-to-end productionalized data science models, ideally solving problems related to areas above on challenging real world data
    • 2+ years of experience with production-level scripting in Python (e.g., statsmodels, scikit-learn), as well as processing, filtering, aggregating large quantities (millions of rows) with data querying languages (e.g. SQL, Hadoop/Hive). 
    • Working knowledge of production ML tools (e.g. Airflow, Spark, Databricks, Azure, AWS, Google Cloud) and statistical tools (e.g., Python, R, Stan, or JAGS)
    • Causal inference related patents, publications, conference presentations, academic papers, or other indicators or scientific expertise and proficiency 
    • Ability to drive clarity on the best modeling or other solution from R&D to implementation
    • Proven ability to think creatively, learn quickly, work independently, manage ambiguity, and adapt to change in a fast-paced environment 
    • Excellent written, verbal, and interpersonal communication skills 
    • Collaborate, collegial, eager to learn, and passion for impact 
    • Authorization to work in the U.S. for any employer

About Us:
At Shelf Engine, you will join an inclusive team of driven, passionate, and caring people hungry for change in an untapped industry. Our founders are well versed in the food industry and have successfully built product and engineering teams. We’re not only solving complex technical problems at scale but tackling key initiatives with large environmental impacts. We're a tight-knit and passionate team that is determined to disrupt a massive industry and leave behind a positive legacy for generations to come.
Shelf Engine is an equal opportunity employer and does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.