Senior Data Scientist, First Line Risk

Block

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
San Francisco, CA
Salary
$198,000–$297,000 / yr
Posted
5 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $170k
This role $248k
$100k $318k
below market most similar roles pay here above market

This role pays more than 96% of similar roles. Most pay $135,000–$205,531 — the blue band above. At the midpoint, this role pays about $248k versus about $170k for comparable roles.

Based on 240 similar postings.

Employer

About Block

Block, Inc. (formerly Square) is a financial technology company operating the Square merchant payments ecosystem, Cash App peer-to-peer payments, TIDAL music streaming, and Bitcoin-focused financial services. Industry: Financial Technology & Payments

Block currently has 50 open roles on FindRole.

Listed pay typically runs $207,900–$311,900 across 50 roles with salary data.

Most-posted roles

View all roles at Block

At a glance

TL;DR · Senior Data Scientist, First Line Risk

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The Senior Data Scientist joins the First Line Risk Data Science team to help manage risks associated with building financial products. This role involves building and scaling a control performance monitoring platform to identify emerging risks and evaluate control effectiveness. You will define actionable metrics, investigate system behaviors to measure coverage, and develop automated monitoring workflows for product governance. Key responsibilities include translating policy objectives into measurement frameworks and leading ambiguous initiatives from problem definition to production. The role requires advanced proficiency in Python and SQL, experience with data warehousing platforms like Snowflake or BigQuery, and knowledge of statistical inference, A/B testing, and anomaly detection. You will also utilize LLMs and engineering prompts to accelerate development while ensuring high-quality data for risk management decisions.

What does a Data Scientist earn in California?

Median $214500 from 136 postings across 32 companies.

See salary data

Skills

Python SQL Snowflake BigQuery Matplotlib Plotly Git LLMs Anomaly Detection Data Warehousing Statistical Inference

What you'll do

  • Define and maintain actionable control performance metrics and key risk indicators to connect risk exposure to clear business decisions.
  • Investigate control performance using source data to measure coverage, enforcement, exceptions, and outcomes.
  • Build and scale automated monitoring modules and workflows within the company's monitoring application.
  • Convert one-off analyses into reusable analytical modules and automated workflows that scale across products.
  • Apply statistical judgment to define populations, cohorts, baselines, and thresholds while managing data quality limitations.
  • Develop repeatable solutions for product governance, including pre-launch risk measurement plans and rollout guardrails.
  • Lead ambiguous initiatives from problem definition through delivery by aligning stakeholders on vision and technical tradeoffs.
  • Communicate complex analytical findings and evidence limitations clearly to technical partners and senior leadership.

What we're looking for

  • Hold a bachelor's degree in a quantitative field with 7+ years of experience, a master's with 5+ years, or a PhD with 3+ years.
  • Possess a track record of leading analytical solutions from problem definition through production use and adoption.
  • Demonstrate advanced proficiency in SQL and Python for building maintainable code, reusable modules, and automated data workflows.
  • Apply strong statistical judgment in areas such as cohort analysis, experimentation, time series, and anomaly detection.
  • Translate business, policy, or control objectives into measurement frameworks to help stakeholders assess performance and take action.
  • Exhibit strong product instincts for internal tools and the ability to prioritize by impact and stakeholder needs.
  • Communicate complex analytical findings, uncertainty, and recommendations clearly to both technical and nontechnical audiences.
  • Have experience in financial technology, risk, compliance, or product governance, or the ability to learn complex domains quickly.

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