Data Scientist Post Sales
AI risk platform that helps financial institutions prevent fraud, ensure compliance, and detect money laundering through behavioral analysis and device intelligence.
Maintainer signals as of 8/12/2026
Funding history
Projects
About Sardine
Sardine helps financial institutions prevent fraud and ensure compliance by analyzing user behavior and device intelligence in real-time. Users can detect identity theft, payment fraud, account takeovers, and money laundering while streamlining KYC/AML processes. Sardine provides risk management with AI agents, case management, and regulatory reporting tools.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will measure, understand, and improve the performance of risk strategies. You will analyze complex datasets, design and track metrics, build and automate self-serve dashboards, and create experiments and ML models to detect fraudulent patterns. You will work with engineers on data instrumentation and translate results into clear, actionable recommendations for stakeholders and clients.
Requirements
- 7+ years of experience in product analytics, business analytics, or data science
- Prior experience in the Fraud/Risk domain
- Hands-on experience in SQL and Python
- Expertise in BI tools such as Tableau, Sigma, Metabase
- Exposure to building ML models to address business challenges
- Ability to perform EDA and cohort analysis and translate them into actionable recommendations
- Proficiency in defining, utilizing, and communicating performance metrics
- Creative problem-solving, strong critical thinking, and results-oriented approach
Responsibilities
- Develop and track metrics to measure and monitor the performance of risk products and risk management strategies
- Conduct in-depth analyses to uncover insights contributing to fraud reduction and higher approval rates
- Translate complex data insights into clear, actionable recommendations for clients
- Build and experiment with ML models to identify fraudulent patterns and enhance detection
- Work with engineers on data instrumentation
- Create and automate self-serve dashboards using BI tools
- Collaborate with cross-functional teams to translate business requirements into data-driven solutions
- Collaborate on implementing risk mitigation solutions aligned with business goals
Benefits
- Equity
- Early exercise for all options including pre-vested
- Remote-first Work from anywhere policy
- Flexible paid time off and year-end break
- Health insurance, dental, and vision coverage for employees and dependents (US and Canada specific)
- 4% matching in 401k / RRSP (US and Canada specific)
- MacBook Pro provided
- One-time home office setup stipend
- Monthly meal stipend
- Monthly social meet-up stipend
- Annual health and wellness stipend
- Annual learning stipend