Block is looking to accelerate the development of automated risk monitoring capabilities across its products by embedding a Product Data Scientist within the First Line Risk Monitoring (FLRM) team. This role will focus on developing key risk indicators (KRIs), risk metrics, and alerting systems to enable proactive risk management and identify opportunities to strengthen controls, instrument monitoring, and automate the detection of emerging risks.
Requirements
- Strong proficiency in Python and SQL. Comfort writing clean, organized, and testable code and contributing to software applications that implement data science and analytical artifacts in pipelines or front-ends.
- Solid understanding of probability and statistics, including A/B test design and evaluation, standard error calculations and statistical inference, and anomaly detection techniques and methods.
- Experience with Python visualization packages (e.g. matplotlib / plotly).
- Experience working with git or version control systems.
- Experience leveraging LLMs and engineering prompts to accelerate development or analyze non-quantitative data.
- Experience with data warehousing platforms (e.g., Snowflake, BigQuery).
- Implement non-experimental analyses (pre/post, synthetic control, regression discontinuity) to estimate changes when experiments are not possible.
Responsibilities
- Collaborate with Risk Business Partners and other stakeholders to develop Key Risk Indicators (KRIs) metrics to measure first-line control performance, identify regressions, and estimate residual risk across Block brands (e.g. Cash App, Square, Afterpay).
- Size opportunities and identify levers to reduce risk or bad activity as measured by KRIs and shape the strategic direction of the Risk organization.
- Utilize proxy measurement methodologies to estimate and monitor operational and product risks at Block.
- Design and implement alerting systems to detect risk regressions and anomalies.
- Create metrics and visualizations that size relative risks, identify priorities, and surface opportunities for action.
- Partner with product teams during experimentation, rollout, and post-launch phases to measure potential product risks.
- Develop experimentable risk metrics and proxies to streamline the measurement of risk outcomes during product launch experiments.
Other
- Minimum 5+ years of post-graduate industry experience in product data science roles. Past experience in Fintech and/or trust & safety is a plus.
- Demonstrated experience building metrics, dashboards, and monitoring systems in fast-paced environments.
- Track record of partnering with cross-functional teams to deliver analytics that drive decision-making.
- Proven ability to communicate complex technical concepts to non-technical stakeholders.
- Strong stakeholder management skills with ability to influence without authority.
