Role overview
The Data Scientist develops machine learning and graph analytics solutions to prevent fraud, evaluate risk strategies, and improve customer outcomes. The role combines client-facing problem-solving with rapid proof-of-concept modeling, production deployment, performance metrics, and business intelligence dashboards for a financial crime prevention platform.
Risk Modeling and Client Impact
- Promote data-driven decisions across internal teams and client engagements.
- Build and deploy fraud prevention models for fintech use cases, taking work from initial prototypes to scalable production solutions.
- Define and monitor metrics that measure risk product performance and the effectiveness of risk management strategies.
- Analyze complex datasets to identify opportunities to reduce fraud and improve client approval rates.
- Work directly with clients to understand fraud challenges and turn analytical findings into clear, actionable recommendations.
- Use data and models to develop risk mitigation strategies and interventions while preserving and improving the user experience.
- Create and automate self-service dashboards with BI tools.
- Partner with engineering to scale models, improve production performance, and support data instrumentation.
- Translate requirements from Business, Product, and Engineering into data-driven solutions.
Required Expertise
- At least seven years in data science, quantitative modeling, or a data-focused role such as product or business analytics, with demonstrated impact in fraud or risk.
- Strong practical experience with Python/R and SQL.
- Expertise in BI platforms such as Tableau, Sigma, or Metabase.
- The ability to structure and analyze complex datasets using exploratory data analysis and cohort analysis, and explain findings to technical and nontechnical audiences, including clients.
- Strong critical thinking and creative problem-solving skills, with a proactive approach to execution.
- Proficiency in defining, tracking, and communicating performance metrics.
- A self-motivated approach, ownership of outcomes, and a strong orientation toward growth.
Preferred Expertise
- Experience with Spark.
Remote Work and Compensation
This full-time position is remote in the United States or Canada, with no office reporting requirement. Employees must maintain a home base in the country where they are hired; flexibility within that country does not extend to unrestricted international work. The distributed team values results over hours worked and supports flexibility around personal commitments.
- USA: estimated annual base salary of $170,000–$210,000 USD.
- Canada: estimated annual base salary of $175,000–$210,000 CAD.
Compensation depends on location. Bonus and equity are additional components, and all options permit early exercise, including before vesting.
Benefits
- Flexible paid time off and a year-end break.
- Health, dental, and vision coverage for employees and dependents in the United States and Canada.
- A 4% match through a 401(k) or RRSP for US and Canadian employees.
- A MacBook Pro delivered to the employee's home and a one-time home office setup stipend for equipment such as a desk, chair, or screen.
- Monthly meal and social meetup stipends.
- Annual health and wellness and learning stipends.
Applicant and employee personal information is handled in accordance with the Applicant and Worker Privacy Notice, which explains processing practices and individual rights.