Note: The job is a remote job and is open to candidates in USA. Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. The Lead Data Analyst will drive data-informed product decisions by delivering actionable insights and designing robust experiments, while collaborating closely with Product, UX, and Engineering teams.
Responsibilities
- Lead experimentation strategy: Design, execute, and analyze A/B tests and quasi-experiments to evaluate product and feature impact on engagement, retention, and customer satisfaction
- Drive product insights: Conduct deep-dive analyses on user journeys, onboarding funnels, feature adoption, and retention cohorts to identify growth and optimization opportunities
- Define and operationalize metrics: Establish north-star metrics, KPIs, and guardrails; ensure consistent definitions across teams and dashboards
- Enable product decision-making: Translate complex analyses into clear, actionable recommendations for product roadmaps and prioritization
- Improve data foundations: Partner with data engineering and platform teams to ensure high-quality telemetry, scalable data models, and reliable reporting layers
- Leverage advanced analytics: Apply statistical techniques (segmentation, cohort analysis, regression, causal inference) to uncover drivers of user behavior and product performance
- Collaborate cross-functionally: Work closely with Product Managers, Designers, and Engineers to embed analytics into the product development lifecycle
- Mentor and elevate analytics practices: Guide analysts on experimentation design, metric definition, and storytelling best practices
- Communicate effectively: Deliver clear, compelling insights to stakeholders and leadership through dashboards, presentations, and narratives
Skills
- 5–8 years of experience in product analytics, advanced analytics, or data science with strong product focus
- Strong experimentation expertise: Hands-on experience designing and interpreting A/B tests and quasi-experimental methods (e.g., difference-in-differences, matching)
- Advanced analytical skills: Proficient in SQL and Python for data analysis; strong foundation in statistics and hypothesis testing
- Product analytics experience: Deep understanding of user behavior analysis, funnel optimization, retention, and feature adoption metrics
- Data visualization & storytelling: Experience with BI tools such as Power BI, Tableau, or Looker to communicate insights effectively
- Telemetry & data modeling knowledge: Experience working with event-based data and defining tracking for digital products
- Business and product acumen: Ability to connect data insights into product strategy and customer experience improvements
- Strong communication and stakeholder management skills, with the ability to influence decisions across teams
- Bachelor's or master's degree in a quantitative field a plus (Statistics, Computer Science, Engineering, Mathematics, or related)
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