About the Role
We are looking for a highly analytical and business-oriented Senior Product Data Analyst to join ourteam. This role is responsible for transforming business needs into measurable insights and scalabledata solutions. The ideal candidate combines strong analytical expertise, experimentation knowledge,business communication skills, and hands-on experience in analytics engineering, data warehousing,and dashboard development.
Success in this role will be measured primarily by measurable business impact and KPIimprovements, not only by report delivery or technical output.
Key Responsibilities
Partner with product, business, finance, to translate business objectives into measurable KPIsand actionable analytical frameworks.
Define, monitor, and optimize product and business health metrics, guardrail metrics, and north-star KPIs.
Design, build, and maintain scalable Data Warehouses (DWH), Data Marts, and analytics datamodels.
Develop and maintain event instrumentation standards, tracking plans, event taxonomies, andmeasurement frameworks across products and systems.
Build automated dashboards and self-service reporting solutions for operational and executivestakeholders.
Perform advanced analytical investigations including segmentation, cohort analysis, funnelanalysis, retention analysis, forecasting, and causal analysis.
Design, execute, and analyze experimentation frameworks and A/B tests, including hypothesistesting, power analysis, MDE calculations, SRM checks, confidence intervals, sequential testing,and multiple comparison corrections.
Apply causal inference and impact measurement methodologies where appropriate.
Ensure scalable, reproducible, and trustworthy reporting through strong data quality practices.
Communicate analytical findings and strategic recommendations clearly to technical and non-technical stakeholders.
Translate complex analytical insights into actionable business and product recommendations.
Identify opportunities to improve customer experience, conversion, retention, operationalefficiency, and revenue growth through data insights.
Performance Expectations (KPIs)
Performance in this role will be evaluated based on:
Impact on product and business KPIs
Adoption and effectiveness of dashboards and analytical solutions
Scalability and reliability of data warehouse and reporting systems
Quality of experimentation and analytical recommendations
Stakeholder satisfaction and communication effectiveness
Required Skills & Qualifications
Statistical & Analytical Expertise
Strong foundation in statistics and experimentation methodologies
Hands-on experience designing, running, and analyzing A/B tests at scale.
Strong understanding of experimentation pitfalls such as SRM, peeking effects, novelty effects,and metric sensitivity.
Experience with forecasting, segmentation, cohort analysis, funnel analysis, retention analysis,and incrementality measurement.
Strong understanding of KPI frameworks, guardrail metrics, and north-star metrics.
Technical Skills:
Expert-level SQL and strong experience with relational databases.
Strong proficiency in Python for analytics, experimentation, automation, and data processing.
Experience with Python libraries such as pandas, scipy, and statsmodels.
Hands-on experience building scalable Data Warehouses, Data Marts, and ETL/ELT pipelines.
Strong understanding of:
Data modeling
Event-tracking architectures
Instrumentation standards
Event taxonomy design
Experience with BI and dashboarding tools such as Tableau, Looker, and Power BI.
Experience with modern data stack and analytics engineering tools including dbt, Dagster, GreatExpectations, and DataHub.
Awareness of GitOps workflows and CI/CD pipelines.
Experience working with modern cloud and data platforms such as OCI, Databricks, GCP,ClickHouse, and BigQuery.
Nice to have: familiarity with experimentation and feature flagging platforms such as Eppo,Statsig, LaunchDarkly, or Optimizely.
Business & Communication Skills
Strong business acumen with the ability to connect analytical insights to measurable businessoutcomes.
Ability to define decision-grade KPIs and analytical frameworks aligned with business objectives.
Strong communication and data storytelling skills for technical and non-technical audiences.
Proven ability to influence product and business decisions through data-driven recommendations.
Experience collaborating with product, finance, commercial, and leadership stakeholders.
Ability to translate ambiguous business problems into structured analytical solutions.
Strong stakeholder management and prioritization skills.
Qualifications:
Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering,Economics, Mathematics, or a related quantitative field.
5+ years of experience in product analytics, business analytics, data science, or applied statistics.
GCC or Saudi market experience is a plus.
Preferred Qualifications
Experience with causal impact measurement techniques such as:
Difference-in-Differences
Synthetic Control
Incrementality Testing
Knowledge of sequential testing and multi-armed bandit methodologies.