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Product Data Analyst, SQL, Python
HelloFresh. Translate product and business requirements into analytical questions and deliver actionable insights .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Proficient in SQL and Python for data analysis and automation, with a strong understanding of statistical methods and A/B testing. Capable of building data pipelines, creating dashboards, and generating actionable insights from complex datasets.
Highest-signal resume keywords
SQL ProficiencyPython ExpertiseStatistical AnalysisData VisualizationData Pipeline Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
SQLPythonPandasNumPyScikit-learnStatistical MethodsA/B TestingData AnalysisETL ProcessesData Validation
Soft Skills
CollaborationProblem-SolvingCommunication
Tools & Technologies
TableauPower BILooker
Industry Keywords
Data AnalyticsBusiness MetricsUser BehaviorProduct PerformanceActionable Insights
Tech Stack
Tools & technologiesETLNumpyPandasPythonScikit-LearnSQLTableau
About the role
Key responsibilities & impact- Translate product and business requirements into analytical questions and deliver actionable insights
- Analyze product performance, user behavior, and business metrics using SQL, Python, and statistical techniques
- Build data pipelines, automation scripts, and analytical tools
- Create self-service dashboards and reports
- Apply data validation and quality checks to ensure accuracy and integrity
- Analyze A/B tests and product changes to measure impact
- Collaborate with Product, Data, Business, leadership, and cross-functional stakeholders to present findings and recommend next steps
- Document analytics projects, tools, and methodologies
- Own analytical deliverables and keep them accurate, relevant, and aligned with business needs
- Provide ad-hoc analyses and deep dives on strategic questions
Requirements
What you’ll need- Proficient in SQL for data extraction, transformation, and analysis
- Experienced in Python, including Pandas, NumPy, and Scikit-learn, for data analysis, modeling, and automation
- Solid understanding of statistical methods and A/B testing
- Skilled in data visualization tools such as Tableau, Power BI, or Looker
- Experienced in building and maintaining data pipelines and ETL processes
- Ability to translate business questions into analytical frameworks and structured problem-solving approaches
- Experience analyzing product performance, user behavior, and business metrics
- Ability to generate actionable insights and data-driven recommendations from complex datasets
Benefits
Comp & perks- Long Service Benefits (anniversary bonus)
- Mental health support
- HMO medical coverage
- Generous leave benefits
- Life insurance for the employee and family
- Annual learning and development budget
- Access to the 360 Learning platform
- Supportive environment prioritizing work-life balance and personal time