Data Analyst – LockedIn AI

Role Overview

We are looking for a curious, analytical, and detail-oriented Data Analyst to transform LockedIn AI’s data into actionable insights that influence product decisions, business strategy, and AI improvements.

This is a high-impact analytics role where you will answer important business questions: How are users engaging with our platform? Which features create the most value? How can we improve AI performance? What drives retention and growth?

You will work across product analytics, user behavior, AI performance, growth, revenue, and operations. Your work will directly impact what we build, how we measure success, and how we improve a platform used by more than 1 million users.

The ideal candidate combines strong technical analytics skills with business understanding. You don’t just analyze numbers — you uncover patterns, explain why they matter, and recommend actions that drive meaningful outcomes.

Key Responsibilities
Product & User Analytics
Analyze user behavior to understand product adoption, engagement, retention, and growth opportunities.
Build and maintain product analytics including funnels, feature adoption metrics, user cohorts, and churn indicators.
Conduct deep analysis to identify what drives user success and where improvements are needed.
Segment users based on behavior, engagement, and use cases to support product and marketing strategies.
Experimentation & A/B Testing
Design and analyze A/B tests and product experiments with statistical accuracy.
Partner with product and engineering teams to define experiment goals, success metrics, and measurement strategies.
Evaluate experiment outcomes and provide actionable recommendations.
Build repeatable frameworks for faster and more effective experimentation.
Business Intelligence & Reporting
Create dashboards and automated reports that provide visibility into business and product performance.
Define and track important KPIs including growth, activation, retention, revenue, engagement, and AI performance.
Deliver weekly reports, business reviews, and ad-hoc analysis for leadership teams.
Maintain consistent metric definitions and ensure teams have trusted data sources.
AI Performance Analytics
Analyze AI system metrics including accuracy, response quality, latency, cost, and user satisfaction.
Monitor AI feature performance and identify opportunities for improvement.
Evaluate the impact of model updates, prompt improvements, and AI releases.
Collaborate with AI teams to create evaluation frameworks and quality benchmarks.
Growth & Revenue Analytics
Analyze acquisition channels, marketing performance, and conversion funnels.
Conduct cohort analysis, lifetime value analysis, and churn research.
Support pricing and monetization decisions using data-driven insights.
Measure the impact of growth initiatives, onboarding improvements, and engagement campaigns.
Data Quality & Collaboration
Ensure accuracy and reliability of data sources and reporting systems.
Identify data issues and work with engineering teams to improve data quality.
Document analytics processes, dashboards, and metric definitions.
Collaborate with product, engineering, marketing, and leadership teams to identify analytics opportunities.

Experience
3+ years of experience in data analysis, product analytics, or related roles.
Experience building dashboards, analyzing experiments, and delivering actionable insights.
Strong experience working with SQL, analytics tools, and statistical methods.
Experience collaborating with cross-functional teams.
Startup or high-growth company experience is preferred.
Education
Bachelor’s degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or a related quantitative field.
Strong analytical ability and proven experience are valued over formal credentials.
Technical Skills
Advanced SQL skills including:
Complex joins
Window functions
CTEs
Query optimization
Experience with Python or R for:
Data analysis
Statistical modeling
Data visualization
Experience with BI tools such as:
Looker
Tableau
Metabase
Mode
Power BI
Understanding of statistical methods including:
Hypothesis testing
Regression analysis
Cohort analysis
Experimental design
Familiarity with data warehouses such as:
Snowflake
BigQuery
Redshift
Strategic & Soft Skills
Strong analytical mindset with the ability to discover meaningful insights.
Excellent communication skills with the ability to explain complex data clearly.
Business-oriented thinking with an understanding of product and growth metrics.
Ability to work independently and take ownership of analytics projects.
Curiosity and willingness to explore new questions beyond assigned tasks.