Data Scientist - Risk

1 month ago
Full-time
Senior
Data Science and Analytics
Block

Block

Block is a company that consists of Square, Cash App, Spiral, TIDAL, TBD, and foundational teams. They are focused on economic empowerment by creating tools to expand access to the economy. Square helps sellers run and grow businesses, Cash App redefin...

Capital Markets
10K-50K
Founded 2009

Description

  • Collaborate with Risk Business Partners and stakeholders to develop Key Risk Indicators (KRIs) and metrics to measure first-line control performance and estimate residual risk across Block brands.
  • Size opportunities and identify levers to reduce risk or bad activity as measured by KRIs and inform the strategic direction of the Risk organization.
  • Design and implement alerting systems and anomaly detection to detect risk regressions and emerging threats.
  • Create metrics and visualizations that quantify relative risks, surface priorities, and identify opportunities for action.
  • Partner with product teams during experimentation, rollout, and post-launch phases to measure and monitor potential product risks.
  • Develop experimentable risk metrics and proxy measurements to streamline risk evaluation during product launches and experiments.
  • Implement non-experimental causal analyses (pre/post, synthetic control, regression discontinuity) when experiments are not possible to estimate changes in risk.
  • Work with stakeholders to quantify potential risks of new features and provide data-driven recommendations and tradeoff analysis.
  • Analyze and build visualizations for externally shared data and support partner risk monitoring through data analysis and monitoring frameworks.
  • Scope analytics projects with First Line Risk Monitoring leads and independently deliver analyses and presentations to senior and non-technical audiences.

Requirements

  • Minimum 5+ years of post-graduate industry experience in product data science roles; Fintech and/or trust & safety experience is a plus.
  • Bachelor’s degree required in Data Science, Statistics, Computer Science, Mathematics, Engineering, or related quantitative field; Master’s degree or PhD preferred in a quantitative discipline (or BA/BS with significant demonstrable advanced data science experience).
  • Demonstrated experience building metrics, dashboards, and monitoring systems in fast-paced environments.
  • Proven track record partnering with cross-functional teams and strong stakeholder management with ability to influence without authority.
  • Ability to communicate complex technical concepts to non-technical stakeholders and present findings to senior audiences.
  • Proactive, self-starting mindset with ability to independently scope and deliver analytics projects.
  • Strong proficiency in Python and SQL, including writing clean, organized, testable code and contributing to data pipelines or front-ends.
  • Solid understanding of probability and statistics, including A/B test design and evaluation, standard error calculations, statistical inference, and anomaly detection methods.
  • Experience with Python visualization libraries (e.g., matplotlib, plotly), version control systems (git), and data warehousing platforms (e.g., Snowflake, BigQuery).
  • Experience leveraging LLMs and prompt engineering to accelerate development or analyze non-quantitative data (preferred).

Benefits

  • Salary ranges (US zones): Zone A $163,600–$245,400; Zone B $155,400–$233,200; Zone C $147,300–$220,900; Zone D $139,000–$208,600 (starting pay varies by location, skills, experience).
  • Remote work options (remote-first work language noted in benefits).
  • Medical insurance (health coverage offered).
  • Flexible time off / PTO policies.
  • Retirement savings plans.
  • Modern family planning benefits.
  • Inclusive interview experience with reasonable accommodations available for disabled applicants during the recruitment process.

Interested in this position?

Apply directly on the company website

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