Associate Fraud Strategy Data Scientist

Job Title: Data Professional Location: Onsite San Jose CA Salary Range: $50 w2.... w2 only Introduction We are seeking a talented and dedicated Data Professional to support the Fraud Risk Strategy team. This role focuses on fraud detection, risk analysis, and loss mitigation by leveraging advanced analytics, predictive modeling, and visualization tools. The ideal candidate combines strong technical skills with business acumen to deliver actionable insights and strategies that protect both the company and its customers. Required Skills & Qualifications • Maximum 2 years of experience in risk analytics, data analysis, or data science • Bachelor’s degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field (or equivalent experience) • Proficiency in SQL, Python, and Excel (including key data science libraries) • Experience with data visualization using Tableau and/or AWS QuickSight • Ability to analyze large datasets to drive actionable insights • Strong knowledge of statistics and data science applications for business problems • Clear communication skills, including the ability to present complex findings to both technical and business audiences • Comfortable managing ambiguity while driving toward business outcomes Preferred Skills & Qualifications • Experience with data models and rule development • Knowledge of project management practices • Familiarity with fraud investigations, fraud typologies, and payment rule systems • Experience collaborating with machine learning teams Day-to-Day Responsibilities • Design and implement fraud detection and mitigation rules • Develop Python scripts and predictive models to support fraud strategies • Investigate fraud cases, perform root cause analysis, and recommend solutions • Set and refine risk strategies for various fraud types • Partner with product and engineering teams to improve fraud control capabilities • Build and present dashboards and visualizations to track fraud KPIs • Provide actionable recommendations to stakeholders at multiple levels Expected Outcomes (6–12 Months) • Collaborate with stakeholders to design and manage fraud strategies and rules addressing emerging fraud trends • Utilize analytics to create real-time, scalable fraud solutions that balance risk mitigation with customer experience • Deliver business recommendations through effective presentations and reporting to leadership and cross-functional teams • Develop dashboards and visualization tools to track key performance indicators (KPIs) for fraud strategies Benefits & Culture We are committed to building a collaborative, innovative environment where data-driven decisions and fraud prevention strategies create measurable impact. #TECH #Onsite