Job Title: Data Scientist Risk and Fraud

Job Location: Remote Ithaca, New York

Job Type: Contract W2

Job Description

What's the role?

As a data scientist, in Trust and Safety, you will be instrumental in enabling a data-driven strategy to detect and reduce risk. This role will be responsible for conducting analyses and creating data models that scale our ability to write and evaluate rules to detect risk and fraud. You will partner with our product and operational teams to understand risky behaviors and leverage your knowledge of data and statistical modeling to translate hypotheses into tools to improve our detection.

What's this team like at?

• Data scientists at use rigorous methods to generate insights that inform product, engineering, and business decisions across the company. We collaborate with partner teams through all stages of development: actively uncovering opportunity areas, crafting experiments to test hypotheses, analyzing the impact of our efforts, and highlighting takeaways

What does the day-to-day look like?

• Work closely and collaboratively with leaders in Trust and Safety controls & detection teams and analytics teams to understand how risk manifests on.
• Present options for how to model various risks to Risk & Fraud leadership and explain tradeoffs to technical and non-technical audiences.
• Create statistical models that enable to better identify risky behaviors, leveraging skills such as regression, clustering, and time series analysis, just to name a few.
• Of course, this is just a sample of the kinds of work this role will require! You should assume that your role will encompass other tasks, too, and that your job duties and responsibilities may change from time to time at discretion, or otherwise applicable with local law.

Qualities that will help you thrive in this role are

• 4+ years experience as a data scientist or data analyst during which you extracted insights from large datasets. 2+ years working in a risk and fraud environment
• Mastery of SQL, proficiency in R/Python, and experience in Looker, Spark, or other data visualization software.
• You are an expert in sophisticated analyses and have experience with advanced statistical methods (ex. Propensity Score Matching, Causal Impact, Regression Models).
• You are adept at communicating your insights, verbally, visually, and in writing to peers and leaders at all technical comprehension levels. You are able to distill complex findings into impactful