Senior Data Scientist - Fraud & Risk (Remote)

Sardine; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Remote-first culture

Equity compensation

MacBook Pro provisioning

Job summary

Sardine is seeking a data-driven professional to measure, understand, and improve risk strategies. You will design and deploy data-driven solutions with real-world impact, working with clients to address fraud challenges and prototype models that scale to production. You will build dashboards and collaborate across teams to drive decisions and outcomes.

This hands-on, high-impact role sits at the intersection of data science, client-facing problem solving, and real-time risk management.

Qualifications

• 7+ years of experience in data science, quantitative modeling, or a data-focused role with high impact in fraud or risk contexts.
• Strong hands-on experience with Python/R and SQL is essential, Spark is a nice to have.
• Expertise in BI tools such as Tableau, Sigma, or Metabase.
• Proven ability to structure and analyze complex data and communicate findings to technical and non-technical audiences.
• Sharp critical thinking and creative problem-solving with a bias toward action.

Responsibilities

• Champion a data-first approach across internal teams and client engagements.
• Build and deploy machine learning models to prevent fraud across fintech use cases.
• Develop and track metrics to measure performance of risk products and risk management strategies.
• Conduct in-depth analyses to uncover insights for fraud reduction and higher client approvals.
• Work directly with clients to translate data insights into actionable recommendations.
• Create and automate self-serve dashboards leveraging BI tools.
• Collaborate with engineering to scale models into production and optimize performance.

Skills

Data science

Quantitative modeling

Python

R

SQL

Spark

BI tools

Tools

Spark

Tableau

Sigma

Metabase

Job description

Sardine is seeking a data-driven professional to measure, understand, and improve risk strategies. You will design and deploy data-driven solutions with real-world impact, working with clients to address fraud challenges and prototype models that scale to production. You will build dashboards and collaborate across teams to drive decisions and outcomes.

This hands-on, high-impact role sits at the intersection of data science, client-facing problem solving, and real-time risk management.