Manager, Data Analytics

MANAGER, DATA ANALYTICS

Current is a leading consumer fintech platform transforming financial access for everyday Americans with over five million members. We provide access to financial solutions that seamlessly work together to solve the needs of our members and enable all Americans to build better financial futures. Based in NYC, our results‑driven environment drives us to build better products, grow faster and empower everyone on our team to have an impact on our business and mission to improve financial outcomes.

We are looking for a hands‑on analytics leader to guide our data and business analytics strategies and manage high‑performing teams. This pivotal role involves driving business growth and enhancing the entire customer lifecycle experience. Serving as a key strategic partner to departmental leaders, the Lead/Manager, Data Analytics will leverage data to inform crucial decisions, optimize operations, and pinpoint opportunities for growth and efficiency.

This role will lead a team of talented analysts, working cross‑functionally to launch new products, scale existing offerings, and fuel business growth. By deeply understanding customer behaviour, you will ensure a seamless user experience and inform strategies that enhance member value.

In this hands‑on leadership role, you will enforce functional processes and best practices while driving the development of analytical projects. You will be responsible for reviewing the work of your team, providing structural guidance on complex analyses, and developing talent strategies to ensure ongoing success. Your experience in experimentation frameworks, business intelligence, and deep‑dive analytics will be instrumental in shaping the future of financial products at Current.

• Lead and mentor a team of data analysts, fostering a culture of analytical excellence by reviewing work, structuring complex analyses, and providing actionable feedback.
• Partner with product managers, business leaders and engineering to design, implement and analyze experiments.
• Deliver timely insights and reporting that identify key business performance drivers and uncover untapped growth opportunities for the leadership.
• Partner with stakeholders across Product, Analytics Engineering and Engineering to design robust data models and define data requirements.
• Enforce functional processes, best practices and data governance to ensure data integrity, accuracy and consistency across all reporting and analyses.
• Enable the development of analytics models, segmentation and personalization strategies to optimize P&L growth and retention.
• Collaborate with Analytics Engineering to build scalable data pipelines and models.
• Partner with Finance and Business Leads on revenue forecasting, growth projections and business case validation.
• Effectively manage team resources and personal bandwidth to prioritise and deliver high‑quality analytical projects in a fast‑paced environment.

• 7+ years of experience in data analytics, with 3+ years specifically managing and leading high‑performing analytics teams.
• Strong hands‑on proficiency in SQL and Python for data analysis, automation and statistical inference.
• Proficient in designing, analysing and interpreting A/B and multivariate experiments.
• Proven ability to uncover revenue and growth opportunities through deep‑dive behavioural analytics and customer segmentation.
• Skilled in developing compelling dashboards and reports to communicate complex insights effectively to non‑technical stakeholders.
• Experience working closely with Product, Marketing, Finance and Engineering teams to roll out features and track impact.
• Strong knowledge of statistical significance testing, forecasting methods and data modelling best practices.
• Track record of improving conversion and retention through data‑driven product strategies.
• Experience building and enforcing standard operating procedures (SOPs) for analytics teams.

• Experience in fintech, B2C products or customer‑centric tech industries.
• Familiarity with financial services or credit risk domain and data.
• Exposure to machine learning modelling workflows…