Head of Data Science - Pricing Modelling
# Head of Data Science - Pricing Modelling **Company Confidentials** · Singapore · `On-site` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Indeed* --- ### About the Role About the Role As a Head of Data Science, you will lead the development of advanced data science and machine learning solutions that optimize pricing, allocation, and fulfillment strategies across our platform. You will tackle some of the company's most complex business problems, driving measurable impacts on customer experience, operational efficiency, profitability, and marketplace health. This role combines deep technical expertise with strategic business thinking. You'll partner closely with Product, Engineering, Operations and Commercial teams to design scalable optimization systems, develop predictive models, influence product strategy, and shape the long-term vision of our marketplace intelligence capabilities. Key Responsibilities Develop dynamic pricing models that balance customer value, demand elasticity, profitability, and competitive positioning. Design pricing algorithms using econometric modeling, causal inference, reinforcement learning, or optimization techniques. Evaluate pricing experiments and quantify business impact through rigorous statistical analysis. Build pricing simulators to forecast revenue, margin, and customer behavior under different pricing strategies. Partner with Product and Business teams to establish pricing guardrails and governance. Design intelligent allocation algorithms to optimize supply-demand matching. Develop optimization models for inventory allocation, merchant assignment, workforce distribution, or resource planning. Improve allocation efficiency using mathematical optimization, operations research, and machine learning. Analyze marketplace dynamics and identify bottlenecks affecting fulfillment quality. Build predictive models for delivery time estimation, order completion, cancellation risk, and fulfillment capacity. Identify opportunities to reduce fulfillment costs while maintaining customer satisfaction. Design decision-support systems that optimize operational workflows. Lead development of production-grade ML models from ideation to deployment. Design large-scale experimentation frameworks and causal analysis methodologies. Define long-term data science roadmap for Pricing and Fulfillment. Serve as the technical authority for complex modeling approaches. Mentor senior data scientists and promote best practices across the organization. Drive adoption of experimentation culture and evidence-based decision making. Key Requirements Master's or PhD in Data Science, Statistics, Computer Science, Mathematics, Operations Research, Economics, or a related quantitative field. 8–12+ years of experience in Data Science, Machine Learning, Applied Research, or Quantitative Modeling. Demonstrated success delivering production-grade ML solutions that drive measurable business outcomes. Strong programming skills in Python and SQL. Expertise in statistical inference, predictive modeling, and experimentation. Experience working with large-scale datasets in cloud environments. Preferable to have experience in ride hailing company Work Location: In person
Наблюдалась 2026-09-21, впервые 2026-09-21, источник — Indeed.