ABOUT EARNIN As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for those with the unique needs of living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks. Since our founding, our app has been downloaded over 13M times and we have provided access to over $15 billion in earnings.
We're fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We're growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey. This is a Palo Alto (Headquarters) based position that will require a minimum of 3 days a week in the office Position Overview: The Vice President of Analytics will lead the analytics function, providing strategic direction and oversight for product, marketing, and risk analytics, as well as all business functions. This senior leadership role is pivotal in driving data-driven decision-making across the organization, ensuring the company leverages data to optimize performance, innovate, and achieve business goals for direct-to-consumer and business environments.
Key Responsibilities: Strategic Leadership: Develop and implement the overall analytics strategy in alignment with the company's business objectives. Lead and mentor a high-performing team of data scientists, analysts, and business intelligence professionals. Collaborate with executive leadership to identify and prioritize analytics initiatives to drive business growth. Ability to predict and analyze impact across various business functions, including product, marketing, engineering, compliance, risk, etc. Product Analytics: Oversee the development of product analytics to understand user behavior, product performance, and opportunities for improvement. Work closely with product management and development teams to provide data-driven insights that inform product roadmap and feature enhancements. Marketing Analytics: Lead the marketing analytics function to strategize, measure, and optimize the effectiveness of full-funnel marketing campaigns to drive growth. Utilize advanced analytics techniques to segment customers, predict behaviors, and enhance targeting strategies. Develop and track key marketing metrics to inform decision-making and demonstrate ROI. Risk Analytics: Manage the risk analytics team to identify, assess, and manage risks across various business functions. Develop predictive models and risk assessment tools to support underwriting, fraud detection, and credit risk management. Ensure compliance with regulatory requirements and internal policies related to risk management. Business Insights: Drive the creation of comprehensive business insights reports and dashboards to inform strategic planning and operational efficiency. Partner with cross-functional teams to gather requirements and deliver actionable insights. Foster a data-driven culture within the organization by promoting the best data analysis and interpretation practices. Innovation and Technology: Stay abreast of emerging analytics tools, technologies, and methodologies to ensure the company remains at the forefront of the industry. Lead the implementation of advanced analytics platforms and infrastructure to support scalable data solutions. Basic Qualifications: Bachelor's degree in Data Science, Statistics, Economics, Business Administration, or related field or equivalent experience 10+ years of experience in analytics 5+ years in a senior leadership role A deep understanding of statistical analysis (e.g., hypothesis testing, experimentation, regressions) Proven track record of developing and executing successful analytics strategies. Strong expertise in product, marketing, and risk analytics Excellent leadership, communication, and interpersonal skills. Ability to translate complex data insights into actionable business recommendations. Strong problem-solving skills and a strategic mindset. Preferred Qualifications: A strong quantitative background acquired through a degree in a related field (e.g., Statistics, Economics, Applied Mathematics) or through professional experience Experience working in the Fintech or Financial Services industry Hands-on proficiency in advanced analytics tools and programming languages such as SQL, Python, R, and data visualization software Hands-on knowledge of machine learning model building and performance analysis
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