Data Scientist

Position: Data Scientist Location: Remote - US Based Duration: 12 month contract + extensions Pay:$47/hr. Position Overview We are seeking a Senior Risk Strategy Analyst to drive risk strategy development, fraud prevention, and portfolio performance optimization for a fast-growing fintech organization. This individual will leverage data, analytics, and automation to identify emerging risks, improve customer outcomes, and support business growth. The ideal candidate combines deep fraud or credit risk expertise with strong technical skills in SQL and Python and has a proven track record of building data-driven strategies within fintech, e-commerce, payments, or lending environments. Key Responsibilities • Develop, maintain, and optimize fraud and credit risk strategies to achieve business performance objectives. • Analyze large and complex datasets using SQL, Python, statistical methods, and data science techniques to identify trends, risks, and opportunities. • Design, implement, and refine automated monitoring rules, risk controls, and decision strategies across the customer lifecycle. • Build dashboards, performance reporting, and monitoring tools using Tableau and other BI platforms to provide actionable insights to business stakeholders. • Partner with Product, Engineering, Operations, and Risk teams to define requirements and execute strategic initiatives. • Identify emerging fraud patterns, risk exposures, and process improvement opportunities and recommend data-driven solutions. • Lead complex investigations and analytical projects to support business decision-making. • Mentor junior analysts and contribute to the development of team best practices. Required Qualifications • 5+ years of experience in Fraud Strategy, Credit Risk Strategy, Risk Analytics, or related roles within: • Fintech • E-commerce • Online Payments • Lending or Financial Services • Advanced SQL and Python skills with experience working with large-scale datasets. • Strong knowledge of statistical analysis, risk modeling, and data science methodologies. • Experience developing and deploying data-driven business rules, monitoring frameworks, and automated risk controls. • Demonstrated ability to solve complex business problems and drive measurable outcomes through analytics. • Exceptional communication skills with the ability to present findings to both technical and non-technical audiences. • Experience building dashboards and reporting solutions using Tableau or similar BI tools. Preferred Qualifications • Experience with experimental design, A/B testing, and data governance. • Knowledge of fraud typologies, including onboarding fraud, synthetic identity fraud, account takeover, and abuse prevention. • Experience supporting customer management, collections, or portfolio strategies for credit products such as revolving credit cards, merchant cash advances, or lending products. • Familiarity with machine learning applications in fraud detection and risk management.