We are looking for a Full Stack Data Science and Analytics professional to join our team. This is a hybrid role designed to bridge the gap between deep statistical modeling and agile product growth. The ideal candidate will handle the end-to-end data lifecycle: from maintaining robust data ingestion/quality to building sophisticated predictive models and leading product experimentation (A/B testing) to drive user engagement and business efficiency.
Your day To Day
- Data Science & Modeling
- Predictive Modeling: Create predictive models, statistical reporting, and data analysis methodologies to identify trends in large, complex datasets.
- Cross-Functional Application: Apply analysis to various areas of the business, including but not limited to Market Economics, Supply Chain, Marketing/Advertising, and Scientific Research.
- Forecasting: Use predictive and prescriptive analytics tools to forecast business outcomes using probabilities and defined confidence levels.
- Innovation: Maintain up-to-date knowledge of existing and emerging scientific principles, theories, and techniques to identify and develop innovative solutions and projects.
- GenAI Integration: Leverage the latest developments in Generative AI technologies to improve efficiency in company business processes and automate manual workflows.
- Product Analytics & Experimentation
- Experimentation Lifecycle: Design, execute, and analyze A/B tests and multivariate experiments (MVT). This includes hypothesis generation, sample size calculation, and determining statistical significance.
- User Behavior Insights: Utilize Product Analytics Tools such as Google Analytics (GA4) and Looker to map user journeys, identify drop-off points, and recommend features that increase product stickiness.
- Strategy & Storytelling: Translate complex statistical findings into actionable insights for high-level stakeholders, including senior leadership and the CEO.
Who We're Looking For
- Education: Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Economics, or a related quantitative field.
- Professional Experience: Minimum of 5 years in Data Science, Product Analytics, or a closely related quantitative field.
- Product Mindset: A strong product-first lensthe ability to ask why users behave a certain way, not just what the data says.
- Technical Capabilities: Advanced SQL (CTEs, Window Functions) and Python (Pandas, Scikit-learn, Statsmodels) is a must
- Expert-level proficiency in Product Analytics Tools Ex: Google Analytics (GA4) and Looker.
- Deep understanding of A/B Testing and experimental design (Frequentist or Bayesian) is required
- Advanced Excel (Financial modeling, complex formulas, and data manipulation) is a must
- Experience with time-series analysis (e.g., Prophet, ARIMA) and growth modeling (S-Curves) is a must
- Communication: Exceptional ability to simplify complex technical concepts for non-technical executive audiences.
- Adaptability: Comfort moving between long-term research projects and fast-paced experimentation cycles.
[Not eligible for ERP reward]
#Sampoerna
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