Sardine is hiring a remote Senior Data Scientist!
Sardine builds an agentic risk platform that helps financial institutions and fintechs detect fraud in real time and automate anti-money-laundering operations. The company is hiring a senior data scientist to sit at the intersection of analytics, machine learning, and hands-on client problem solving. In this role you would help measure and sharpen the performance of Sardine's risk strategies while staying ahead of quickly evolving fraud patterns, moving from rapid proof-of-concept prototyping through to durable production systems that use machine learning and graph analytics. Day to day the work blends deep dataset analysis, metric design, dashboard building, and close collaboration with clients and internal teams across business, product, and engineering. Sardine is a remote-first organization with distributed teams, and this position is open to candidates based in the United States or Canada, with pay tied to your location and a requirement to keep your home base in the country where you are hired. The environment suits someone who is self-directed, comfortable owning outcomes, and energized by a fast-moving, high-impact remit rather than a fixed schedule.
Key responsibilities
- Advocate for a data-first mindset across internal teams and client engagements
- Build and deploy machine learning models that prevent fraud across a range of fintech use cases, from proof of concept to production
- Define and track metrics that gauge risk product performance and the effectiveness of risk management strategies
- Run deep analyses that surface insights leading to lower fraud and higher approval rates for clients
- Engage directly with clients to diagnose their fraud challenges and turn complex findings into clear, actionable recommendations
- Support the design of risk mitigation strategies and interventions while protecting the end-user experience
- Create and automate self-serve dashboards using business intelligence tooling
- Partner with engineering to scale models into production, tune performance, and support data instrumentation
- Work with business, product, and engineering stakeholders to convert requirements into data-driven solutions
Key requirements
- 7 or more years in data science, quantitative modeling, or a data-centric role such as product or business analytics, with demonstrated impact in fraud or risk
- Strong hands-on proficiency in Python or R, plus SQL; Spark is a nice to have
- Expertise with BI tools such as Tableau, Sigma, or Metabase
- Ability to structure and analyze complex data using techniques like exploratory data analysis and cohort analysis
- Clear communication of findings to technical and non-technical audiences, including external clients
- Sharp critical thinking and creative problem solving with a bias toward action
- Skill at defining, tracking, and communicating performance metrics
- Seniority: Senior
- Work mode: Remote (US or Canada)
- Key skills: Python, R, SQL, Spark, Tableau, Sigma, Metabase, machine learning, graph analytics, exploratory data analysis, cohort analysis, metrics design, dashboard automation
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