Senior Data Scientist, First Line Risk

Block

. Define and maintain actionable control performance metrics and key risk indicators .

Posted 11/4/2026full-timeRemote • United StatesSenior💰 $168,300 - $297,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in defining and maintaining control performance metrics and risk indicators, with strong analytical skills in SQL and Python for building automated workflows and reusable analytical modules. Proven ability to communicate complex findings and align stakeholders across teams in financial technology and compliance domains.

Highest-signal resume keywords

Advanced Proficiency In SQLAdvanced Proficiency In PythonExperience With Large DatasetsStrong Statistical And Analytical JudgmentExperience In Financial Technology

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Cohort AnalysisExperimentationTime Series AnalysisMonitoring FrameworksStatistical InferenceAnomaly DetectionA/B Test DesignData VisualizationAutomated Data WorkflowsMeasurement Frameworks

Soft Skills

Clear CommunicationStakeholder AlignmentProblem DefinitionTradeoff Decision-MakingCollaboration

Tools & Technologies

Python Visualization PackagesGitData Warehousing PlatformsSnowflakeBigQueryAI Tools

Industry Keywords

Risk ManagementComplianceProduct GovernanceFinancial TechnologyQuantitative Analysis

Tech Stack

Tools & technologies

BigQueryPythonSnowflakeSQL

About the role

Key responsibilities & impact

Define and maintain actionable control performance metrics and key risk indicators
Investigate controls using source data and system behavior to measure coverage, enforcement, exceptions, and outcomes
Identify incomplete instrumentation or evidence
Contribute scalable monitoring metrics and modules to the monitoring application
Connect metrics to risks and controls and prioritize consequential monitoring gaps
Turn one-off analyses into reusable analytical modules and automated monitoring workflows
Define populations, cohorts, baselines, and thresholds and calibrate monitoring
Build pre-launch risk measurement plans, rollout guardrails, and post-launch monitoring
Partner with internal users to understand decisions and workflows and shape the monitoring roadmap
Lead ambiguous initiatives from problem definition through delivery
Align stakeholders on vision, tradeoffs, ownership, and actions
Communicate findings and evidence limitations to technical partners, control owners, compliance teams, and senior leaders
Contribute reusable methods and technical guidance for other data scientists

Requirements

What you’ll need

Bachelor's degree in statistics, data science, economics, computer science, or a similar quantitative field with 7+ years of relevant experience; or a master's degree with 5+ years; or a PhD with 3+ years
Track record of leading analytical solutions from problem definition through production use and adoption, including multi-person or cross-team efforts
Advanced proficiency in SQL and Python
Experience working with large datasets and building maintainable analytical code, reusable modules, and automated data workflows
Strong statistical and analytical judgment, including cohort analysis, experimentation, time series, or monitoring
Ability to recognize selection bias, incomplete data, and misleading metrics
Experience translating business, policy, or control objectives into measurement frameworks
Strong product instincts for internal tools
Ability to make practical tradeoffs, build stakeholder alignment, and execute across teams
Clear written and verbal communication of complex analytical findings, uncertainty, and recommendations
Experience in financial technology, risk, compliance, or product governance, or ability to learn complex domains
Experience using AI tools to accelerate analysis and development
Strong proficiency in Python and SQL; clean, organized, and testable code
Understanding of probability and statistics, A/B test design and evaluation, standard error calculations, statistical inference, and anomaly detection
Experience with Python visualization packages such as matplotlib or plotly
Experience with git or version control systems
Experience leveraging LLMs and engineering prompts
Experience with data warehousing platforms such as Snowflake or BigQuery

Benefits

Comp & perks

Remote work
Medical insurance
Flexible time off
Retirement savings plans
Modern family planning
Reasonable accommodations throughout the recruitment process