Product Analytics Engagement Manager

EXL•United States,

4d•$150,000 - $180,000•Hybrid

About The Position

The Product Analytics Engagement Manager will support a personal loan portfolio and drive origination volume by identifying opportunities to increase demand generation through product feature improvements and better application-funnel conversion. The role monitors key performance metrics for business programs and campaigns, investigates changes in performance through root cause analysis, and quantifies the impact of initiatives using A/B testing. This is a hands-on product analytics role focused on customer behavior, product usage, product performance, and measurement across the product lifecycle. The manager develops evaluation frameworks, KPIs, dashboards, reporting, and analytical insights, while improving data tracking and instrumentation and supporting analytics infrastructure. The role partners with Product, Engineering, Data Science, and Business teams to turn findings into actionable product improvements. The position is hybrid, with 2–3 days per week in the San Francisco office.

Requirements

Bachelor’s degree or higher in Engineering, Data Science, Statistics, Computer Science, or a related field.
7+ years of relevant experience in Data Science, Product Analytics, or related disciplines.
Proficiency in SQL and Python, with experience working with large-scale products or event-based datasets.
Experience with data platforms, BI/reporting, and hypothesis testing.
Strong understanding of product performance measurement and evaluation.
Ability to work independently, identify information gaps, and prioritize high-impact initiatives.
Experience working with financial institutions such as banks or fintech companies in analytics.
Strong communication and stakeholder-management skills, including the ability to work across functions.
Strong analytical and problem-solving skills.
Deep expertise in campaign and funnel analytics.

Responsibilities

Design and execute evaluation frameworks to assess product quality, accuracy, and user-intent alignment.
Define, track, and analyze KPIs and success metrics across the product lifecycle.
Perform product analytics to understand customer behavior, product usage, and performance.
Identify data, tracking, and instrumentation gaps and improve measurement capabilities.
Develop and support A/B testing and experimentation to evaluate product strategies.
Support data pipelines, reporting, and analytics infrastructure.
Analyze feature adoption, engagement, retention, and product performance trends.
Develop dashboards, reporting, and analytical insights to support product decision-making.
Partner with Product, Engineering, Data Science, and Business teams to translate insights into actionable product improvements.
Monitor business program and campaign metrics, conduct root cause analyses when performance changes, and quantify initiative impact through A/B testing.
Identify opportunities to increase demand generation and origination volume by improving product features and application-funnel conversion.