Description : Data Scientist (Monetization & Pricing)
Experience : 4 - 6 Years
Industry : E-commerce / Marketplace / Fintech
Role Summary
We are seeking a high-caliber Data Scientist to join our Monetization team. In this role, you will act as a Pricing & Measurement Architect, responsible for establishing the core modeling foundations for pricing, fees, and promotional incentives.
You will bridge the gap between complex economic theories and scalable engineering, building elasticity libraries to quantify demand response and measuring substitution/cannibalization effects across products.
The ideal candidate possesses advanced SQL and Python skills, a deep understanding of Causal Inference, and the ability to translate ambiguous business questions into crisp, measurable analytical plans.
Responsibilities
- Foundational Monetization Modeling : Build and maintain advanced ML models to quantify price elasticity, demand response, and the impact of promotional incentives.
- Causal Inference & Experimentation : Apply advanced experimentation techniques in a product setting, including power analysis, primary/secondary metric design, and hypothesis testing to drive monetization strategy.
- Cannibalization & Substitution Measurement : Develop frameworks to quantify and explain how different products, offers, and promotion types interact and compete within the ecosystem.
- Monetization Optimization : Utilize optimization methods and solvers (e.g., linear programming, constrained optimization) to design efficient fee structures and promotional budgets.
- Advanced Analytics Workflows : Write production-quality SQL and use Python to automate complex data processing, modeling, and analytical workflows.
- Self-Service Intelligence : Build and own complex Tableau dashboards and the supporting data pipelines to enable scalable tracking of monetization KPIs.
- LLM Integration for Analytics : Explore and apply Large Language Models (LLMs) to accelerate insight generation, automate reporting, and augment analytical workflows.
- Root-Cause & Structured Problem Solving : Perform deep-dive analyses to identify the drivers of business performance, translating ambiguous stakeholder questions into actionable metrics.
- Stakeholder Storytelling : Communicate complex technical insights and modeling outcomes clearly to both technical peers and non-technical business leadership in fluent English.
Technical Requirements
- Programming & SQL Mastery : Proven ability to write efficient, production-grade SQL and Python for data science applications.
- Statistical Rigor : 4+ years of experience in structured problem solving, root-cause analysis, and advanced causal inference.
- Machine Learning Profile : Strong orientation in baseline predictive modeling, specifically applied to monetization or pricing analytics.
- Experimentation Excellence : Hands-on experience designing and interpreting complex A/B tests in a fast-paced product environment.
Preferred Skills
- Elasticity Modeling : Ability to build and maintain a library of demand/supply response models.
- Substitution Analysis : Experience in quantifying cross-product substitution and promotional cannibalization.
- Optimization Methods : Exposure to linear programming or constrained optimization for business design.
- Advanced Visualization : Mastery of Tableau for building complex, self-service analytical tools.
- AI Innovation : Exposure to applying LLMs for analytics acceleration and automation.
Core Competencies
- Business Acumen : Ability to align technical depth with monetization goals and revenue growth.
- Clarity of Thought : Excellence in translating ambiguous business requirements into structured analytical roadmaps.
- Technical Depth : A commitment to building foundational frameworks that are scalable and reproducible.
- Result Driven : A focus on delivering measurable impact through pricing optimization and fee design.
(ref:hirist.tech)
