Primary Skills
- Spark - Pyspark, SQL, SQL (Basic + Advanced), Python, Hive, Data Modelling Fundamentals
Specialization
- Data Analysis: Analyst
Job requirements
Product Analyst
As a Product Analyst, you will drive data-informed product decisions by delivering actionable insights, designing robust experiments, and deeply understanding user behavior. You will partner closely with Product, UX, and Engineering to shape product strategy and improve customer experience across security products.
Key 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.
About You
· 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)
Skills Required
- 5-8 years of experience in product analytics, advanced analytics, or data science with product focus
- Strong experimentation expertise designing and interpreting A/B tests and quasi-experimental methods
- Proficiency in SQL for data analysis
- Proficiency in Python for data analysis
- Experience with Spark / PySpark and Hive
- Experience with BI tools (Power BI, Tableau, or Looker) for visualization and storytelling
- Telemetry and event-based data modeling experience
- Strong communication and stakeholder management; ability to translate analyses into product recommendations
- Experience mentoring or guiding analysts on experimentation, metrics, and storytelling
- Bachelor's or master's degree in a quantitative field (Statistics, Computer Science, Engineering, Mathematics, or related)
Brillio Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Brillio and has not been reviewed or approved by Brillio.
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Healthcare Strength — Healthcare is considered comprehensive, including medical coverage for employees and dependents alongside life, disability, and accidental death protections. Feedback suggests these protections are a core strength of the package.
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Leave & Time Off Breadth — Time-off options include paid leave and parental leave, with flexible or ‘flexible PTO’ approaches cited in some contexts. Feedback suggests this breadth helps support work-life balance when team norms permit usage.
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Wellbeing & Lifestyle Benefits — Wellbeing offerings span counseling, financial-management sessions, fitness programs, and travel insurance, plus region-specific extras like discounted IT hardware and work-from-home essentials. Feedback suggests these add-ons enhance perceived value beyond core insurance.
Brillio Insights
What We Do
Brillio is the leader in global digital business transformation, applying technology with a human touch. We help businesses define internal and external transformation objectives, and translate those objectives into actionable market strategies using proprietary technologies. With 2600+ experts and 13 offices worldwide, Brillio is the ideal partner for enterprises that want to quickly increase their core business productivity, and achieve a competitive edge, with the latest digital solutions.


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