What are the responsibilities and job description for the Associate Fraud Strategy Data Scientist position at Brightpath Solutions?
JOB DESCRIPTION:
We are looking for a talented, enthusiastic and dedicated person to support the Fraud Risk Strategy team. The incumbent will support projects in fraud detection, risk analysis, and loss mitigation. This role involves analytics, refining risk strategies, and developing predictive algorithms, preferably within the risk domain.
REQUIREMENTS:
- Maximum 2 years of experience in risk analytics, data analysis, or data science in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.
- Bachelor’s degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining, or related field, or equivalent practical experience.
- Experience using statistics and data science to solve complex business problems.
- Proficiency in SQL, Python, and Excel (including key data science libraries).
- Proficiency in data visualization tools (Tableau preferred).
- Experience working with large datasets.
- Strong communication skills with the ability to present complex results to technical and non-technical stakeholders.
- Comfortable with ambiguity and able to steer analytics projects toward testable hypotheses and action-oriented outcomes.
- Desirable: experience or aptitude in risk-related problems, AWS, knowledge of fraud investigations, payment rule systems, or working with ML teams.
Key Job Functions
- Design and implement detection and mitigation rules for fraud.
- Develop Python scripts and predictive models that support fraud risk strategies.
- Investigate novel or large-scale fraud cases and identify root causes.
- Define and set strategy for different fraud/risk types.
- Collaborate with product and engineering to improve control capabilities and deploy solutions at scale.
- Develop and present strategies, guide execution, and provide actionable recommendations to stakeholders.
- Build dashboards and visualizations to track KPIs and the impact of implemented strategies.
Expected Outcome in 6-12 months
- Work closely with team members and stakeholders to design, develop, and manage effective fraud strategies and rules.
- Utilize data analysis to design and implement strategies that address emerging fraud trends while preserving a positive customer experience.
- Collaborate cross-functionally to deploy data-driven solutions that operate in real time and at scale.
- Provide clear, data-backed recommendations to leadership and present findings across multiple stakeholder levels.
- Deliver dashboards and visualizations to monitor and report on fraud KPIs.
Preferred Skills
- Data analytics and modeling
- Rule development for fraud detection
- Dashboard and visualization creation (Tableau/Quicksight)
- Project management
- Strong written and verbal communication
NOTES:
- Strong SQL proficiency.
- Experience applying statistics and data science to complex fraud mitigation problems.
- Proficiency in AWS Quicksight and Tableau is a plus.
- Role is strictly contract to cover multiple leaves over a 1-year period; potential to extend based on business need and performance.
- Day shift: Monday–Friday, Pacific Time.
- Multiple Zoom interviews (2–3) with an SQL assessment during the first interview.
MUST HAVE:
- Up to 2 years of relevant experience in risk analytics, data analysis, or data science within eCommerce, payments, trust/risk/fraud, or abuse investigations.
- Degree in a quantitative field or equivalent experience.
- Practical experience with SQL, Python, and data visualization (Tableau).
- Proven ability to apply statistics and data science to fraud mitigation challenges and to work with large datasets.
