Associate Data Scientist (Fraud & Risk Strategy)

About the Role: We are seeking a talented, enthusiastic, and dedicated individual to join our Fraud Risk Strategy team. The candidate will work directly on high-impact fraud detection, risk mitigation, and loss analysis initiatives across the company’s payment and trust ecosystem. This is a hands-on role with exposure to strategy, analytics, and cross-functional execution. Job Responsibilities: Design, test, and implement fraud detection and mitigation rules and strategies Build Python scripts, statistical models, and algorithms to support risk controls Investigate novel or large-scale fraud cases; perform root-cause analysis Identify emerging fraud trends and propose proactive defenses Set the strategy and policy approach for various risk types (e.g. account takeover, payments abuse) Partner with product and engineering teams to integrate controls and automation Develop and present data-driven recommendations to stakeholders and leadership Create and maintain dashboards and visualizations to monitor key fraud KPIs Lead end-to-end fraud projects, deploy scalable solutions, and influence business direction Required Skills & Qualifications: 2 years of professional experience in risk analytics, data science, or fraud / trust / user abuse domains (eCommerce, payments, online marketplaces) Bachelor’s degree in Data Science, Mathematics, Statistics, Data Analytics, or a related field (or equivalent hands-on experience) Proven competence using statistics, predictive modeling, and analytical methods to solve business problems Strong proficiency in SQL, Python, and Excel, including data science libraries (e.g. pandas, scikit-learn) Experience building and working with large datasets Skilled in data visualization (especially Tableau) and translating insights into dashboards Ability to clearly explain complex results to technical teams, product leaders, and executives Comfortable navigating ambiguity and driving toward actionable, hypothesis-based outcomes Experience or aptitude in fraud / risk modeling, payments rule systems, or fraud typologies Familiarity with AWS (e.g. Quicksight) or cloud analytics environments Experience working with machine learning teams or deploying models in production Exposure to fraud investigations, product abuse, or real-time decisioning systems Job Type: Contract Pay: Up to $50.00 per hour Expected hours: 40 per week Application Question(s): Are you open to relocate to the job location (San Jose, CA)? Are you either a Green Card holder or US Citizen? Are you open to W2 contract roles? Do you have relevant data science experience in E-Commerce Industry? How many years of work experience do you have with Risk Analytics? How many years of hands-on experience do you have with SQL? Work Location: In person