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Job Summary:
24+ months contract ; Remote role
We are seeking a highly analytical and business-focused Data Scientist with strong expertise in pricing optimization and a solid background in retail. This role will be responsible for developing data-driven pricing strategies, building predictive models, and delivering actionable insights to maximize revenue, margins, and competitive positioning. The ideal candidate will have strong Python programming skills and experience working with large-scale retail data.
Key Responsibilities:
- Develop and implement pricing optimization models to improve revenue, profitability, and market share.
- Analyze large datasets to identify pricing opportunities, demand patterns, and customer behavior trends.
- Build predictive models (e.g., demand forecasting, price elasticity, promotion effectiveness).
- Partner with business stakeholders (merchandising, sales, marketing) to align pricing strategies with business goals.
- Design and execute A/B tests to evaluate pricing strategies and promotional campaigns.
- Develop dashboards and visualizations to communicate insights and recommendations.
- Monitor pricing performance and continuously refine models based on market changes.
- Work with engineering/data teams to deploy scalable pricing solutions in production.
Required Qualifications:
- Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or related field.
- 4+ years of experience in Data Science, with a focus on pricing or revenue optimization.
- Strong background in retail industry (e-commerce, FMCG, or brick-and-mortar).
- Advanced proficiency in Python (Pandas, NumPy, Scikit-learn, PySpark).
- Experience with SQL and working with large datasets.
- Strong understanding of statistical modeling, machine learning, and experimentation techniques.
- Hands-on experience with pricing models such as:
- Price elasticity modeling
- Demand forecasting
- Markdown optimization
- Promotion analytics
