Data Scientist II

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Company Overview: At Snap Finance, we believe everyone deserves access to the things they need, regardless of credit history. Since 2012, we've used data, machine learning, and a more human approach to create flexible financing solutions that help people move forward. We're proud of our inclusive, supportive culture, built on empowering our customers, partners, and team members alike. When our people thrive, so does our innovation. If you're looking to make an impact and grow with a team that values you, come join us! Job Description Snap Finance is looking to strengthen its dynamic, growing analytics department. We are seeking a dedicated Data Scientist with a passion for statistics, experimentation, and solving real-world problems. The ideal candidate is an analytically driven problem solver who can translate data into actionable business insights. In this role, you will partner with Marketing to support customer acquisition, engagement, retention, and lifetime value initiatives across multiple financial products. You'll leverage data science, experimentation, customer segmentation, personalization, and marketing measurement techniques to help drive growth and improve customer experiences. How You'll Make an Impact Customer Insights & Personalization Analyze customer, campaign, and behavioral data to uncover opportunities for customer acquisition, engagement, retention, and growth. Support the development of audience segments and personalization models that enhance customer experiences across digital, paid media, SEO, email, SMS, push notifications, in-app messaging, and direct mail. Partner with marketing teams to better understand customer behavior and identify opportunities to improve campaign performance. Marketing Measurement & Reporting Build and enhance attribution models that measure the incremental impact of marketing activities and customer touchpoints across channels and financial products. Analyze cross-channel marketing performance to identify opportunities for improved targeting, personalization, and return on marketing investment. Communicate attribution findings and performance insights in a clear, actionable manner that informs marketing strategy and business decisions. Experimentation & Optimization Assist in designing, executing, and analyzing experiments to measure the effectiveness of marketing campaigns, customer journeys, and personalization efforts. Evaluate test results and provide recommendations that improve customer acquisition, engagement, retention, and marketing efficiency. Contribute to a culture of continuous learning and optimization through data-driven decision-making. Data Science & Analytics Apply statistical, predictive, and analytical techniques to solve marketing and customer-focused business problems. Build, validate, and refine models that support audience targeting, personalization, customer growth, and retention initiatives. Work with large customer and marketing datasets to generate insights and support business decisions. Collaboration & Stakeholder Partnership Collaborate closely with stakeholders across Marketing, Engineering, Product, and Analytics to understand business needs and deliver meaningful insights. Communicate analytical findings and recommendations in a way that is accessible to both technical and non-technical audiences. Build strong working relationships and develop a deep understanding of the business, customers, and marketing goals. AI & Innovation Leverage AI-powered tools to improve productivity, accelerate analysis, support insight generation, and enhance marketing effectiveness. Explore new analytical approaches and emerging technologies while applying sound business judgment and analytical rigor. Growth & Development We are committed to investing in your growth and development, providing opportunities to expand your technical, analytical, and business skills as you advance your career. As our team and business continue to grow, you'll have the opportunity to take on increasingly complex challenges, broaden your impact, and help shape the future across our organization. What You'll Need to Succeed 2-3 years of experience working in a data science position or performing work that aligns with the required skills in another role. M.S. in a quantitative field such as Statistics, Econometrics, Mathematics, Physics, Computer Science, Quantitative Social Science, Quantitative Finance, or another related field. B.S. in one of the fields described above will be considered if the candidate's skill set and experience are robust. A skilled analyst who produces regular reporting content for key stakeholder meetings, responds to ad hoc analysis requests, and generates insightful deep dives. Familiarity with and experience in consumer finance, digital marketing, SEO, and/or direct-to-consumer marketing. Classification methods such as logistic regression, decision trees, KNN, and random forests. Regression methods such as linear regression, nonlinear

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