Lead Data Analyst

Brillio

Lead Data Analyst at Brillio shaping product strategy through data insights and experimentation. Collaborating with cross-functional teams to improve customer experience across security products.

Posted 7/11/2026full-timeRemote • Texas • 🇺🇸 United StatesSenior💰 $100 - $105 per yearWebsite

Tech Stack

Tools & technologies

PythonSQLTableau

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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)

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Brillio Website LinkedIn All Job Openings 1001 - 5000 employees 🤖 Artificial Intelligence 🔒 Cybersecurity 💰 Private Equity Round on 2019-01 Artificial Intelligence
Consulting
Cybersecurity Brillio is a technology consulting company that specializes in driving digital transformation for businesses across various industries such as banking, financial services, insurance, life sciences, telecom and media, healthcare, and retail. They focus on customer experience transformation, data and AI, product and platform engineering, and provide infrastructure, cloud, and security solutions. With an emphasis on engineering digital products and leveraging generative AI, Brillio aims to provide bespoke solutions that help businesses thrive in the age of AI and technological disruption. They also offer services to help businesses adapt to new technological challenges and turn disruptions into competitive advantages. Lead Data Analyst 🔥 0 minutes ago 🤠 Texas – Remote 💵 $100 - $105 / year ⏰ Full Time 🟠 Senior 📉 Data Analyst 🦅 H1B Visa Sponsor Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
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. 🎯 Requirements
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.
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Hard Skills & Tools

A/B TestingQuasi-Experimental MethodsStatistical TechniquesUser Behavior AnalysisFunnel OptimizationRetention MetricsFeature Adoption MetricsTelemetry KnowledgeData ModelingHypothesis Testing

Soft Skills

Communication SkillsStakeholder ManagementMentoring