Data Scientist, Product Analytics

New York, NY 10116

Category: Data Job Number: 22867

Job Description

Role Overview: As a key member of the Risk & Fraud team, your role will be focused on leveraging data to drive strategic decisions aimed at detecting and mitigating risk across the platform. You will be responsible for conducting detailed analyses, generating insights, and monitoring the health of Risk & Fraud metrics. By utilizing your data visualization and wrangling expertise, you'll partner closely with cross-functional teams to ensure that these metrics are both accessible and reliable.

Team Overview: Our team thrives on applying data-driven methods to guide decisions within product, engineering, and business domains. We work closely with Product and Operations teams to identify opportunities, design experiments, assess outcomes, and extract key insights. We embrace a continuous learning culture, and while prior fraud experience isn't necessary, a strong data-driven mindset and a willingness to adapt and grow will be key to your success.

Daily Responsibilities:

  • Collaborate with Risk & Fraud and Analytics leaders to understand the manifestations of risk on the platform.
  • Develop and communicate clear metrics to track risk health and customer experience, presenting insights to both technical and non-technical audiences.
  • Engage with stakeholders to define the key metrics for risk monitoring and take ownership of analyses and dashboards.
  • Formulate hypotheses, run experiments, and test different scenarios to assess the impact of fraud enforcement on customer experience.
  • Adapt to various tasks and take on new challenges as they arise in this dynamic and evolving role.

Key Qualities for Success:

  • 1-5 years of experience as a data scientist or analyst, with a strong track record of extracting insights from large datasets. Experience in risk and fraud is a plus, but not mandatory.
  • Proficiency in SQL and expertise in Looker are essential; familiarity with Python is a bonus.
  • Strong analytical skills with a deep understanding of business health metrics. Familiarity with statistical methods and experimentation techniques is an advantage.
  • Excellent communication skills, with the ability to present complex findings in a clear, concise, and actionable manner to a wide range of stakeholders.

 

**We are an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, color, ethnic origin, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.**

 

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