Senior Data Scientist - Pricing Strategy

About The Role

Klook is establishing a data-driven Pricing function focused on deriving prices based on evidence instead of intuition. As the Senior Data Scientist in Pricing Strategy, you will lead the development of core analytical and modeling components including dynamic pricing models, price elasticity forecasting, causal measurement tools, and experimental methodologies that reveal true customer response to pricing. You will collaborate across all Klook markets and booking platforms.

This is a hands-on role where you will design and deploy production-grade analytical systems—covering demand and elasticity forecasting and the underlying dynamic pricing logic—rather than delivering isolated analyses. Reporting to the Director of Pricing, you will closely coordinate with Strategy & Operations, Platform & Intelligence, Vertical Planning, Product, and Marketing teams.

Key Responsibilities

• Develop price elasticity models and demand forecasts segmented by product, market, and customer, anticipating trends and converting elasticity insights into actionable price recommendations.
• Build advanced causal measurement methods such as difference-in-differences, synthetic control, and other quasi-experimental approaches to identify genuine impacts of pricing and promotion where traditional A/B tests aren’t possible.
• Accurately quantify uncertainty through confidence intervals and sensitivity analyses to inform leadership about the reliability of estimates.
• Establish and implement rigorous experiment designs, including hypotheses formulation, minimum detectable effect (MDE), power calculations, guardrails, and stopping rules, to improve beyond conventional fixed-window A/B tests.
• Manage pricing experiments including A/B and geo-based switchback tests to assess uplift, selecting meaningful price increments based on elasticity curves.
• Create scalable experimentation standards and templates to ensure trusted results that P&L owners can rely on for rollout decisions.
• Perform thorough exploratory data analyses on pricing, competitor, booking, and margin data to identify opportunities and guide pricing strategies.
• Collaborate with Platform & Intelligence for data collection, mapping, and ensuring data quality and transparency for pricing.
• Design, develop, and operationalize dynamic pricing models optimizing prices across various products, channels, and markets, balancing conversion, revenue, and profit objectives.
• Translate diverse pricing hypotheses into models, such as competitor-based pricing for commoditized offerings and value-based pricing where appropriate.
• Partner with engineering and pricing engine teams to transition models from prototype stage into dependable production systems with monitoring.
• Provide prescriptive pricing recommendations that align with business goals and constraints including margin floors, competitive positioning, and inventory considerations.
• Continuously monitor, backtest, and refine models in production to maintain performance and adapt to market shifts.
• Work closely with cross-functional teams like Vertical Planning, Product, Marketing, and Data to turn analytical findings into strategic guidelines and practical rollout plans.
• Assist in deciding promotion and marketing budgets by measuring lift and incrementality to allocate resources effectively.
• Present insights and results clearly to senior leaders including VP and C-level executives, translating technical findings into business impact and well-supported recommendations.
• Champion data-driven decision making across pricing, promotions, and budgeting with clear, executive-ready written and verbal communication.

Required Qualifications and Skills

• Master’s or PhD in quantitative disciplines such as statistics, economics, computer science, or data science preferred; equivalent practical experience also valued.
• At least five years in data science or quantitative analytics with direct responsibility for pricing, revenue management, demand forecasting, or causal measurement, ideally within marketplaces, e-commerce, travel/OTA, or platform business contexts.
• Solid expertise in causal inference techniques like difference-in-differences, synthetic control, instrumental variables, and uplift modeling, along with a deep understanding of their assumptions and limitations.
• Proven ability to design statistically rigorous experiments from the ground up, considering power, MDE, randomization unit, guardrails, and avoiding common pitfalls such as peeking.
• Strong modeling experience including price elasticity estimation, demand forecasting, and applied statistical or machine learning models (regression, time series, classification, clustering) targeted at pricing or demand prediction.
• Advanced proficiency in Python and SQL, capable of handling large and complex datasets end-to-end.
• Strong communication skills with a record of converting analytics into decisions and influencing non-technical and executive stakeholders.

Preferred Additional Skills

• Experience in OTA or travel sectors, with understanding of travel-specific pricing challenges including perishability, seasonality, rate parity, and supplier influence.
• Track record in model productionization working with engineering or MLOps teams to deploy and maintain pricing or recommendation engines.
• Experience using cloud data warehouse and computing platforms such as BigQuery and common Python data science libraries.
• Familiarity with competitive intelligence data gathering including web crawling and price mapping, as well as bulk-buy and inventory economics.
• Knowledge of modern AI tools and large language models (LLMs), including building reusable AI components, agents, and workflows that enhance team productivity and accelerate personal analysis and communication.

Additional Information

Klook is an equal opportunity employer committed to fostering a diverse and inclusive workplace where employees from all backgrounds thrive. We do not accept unsolicited resumes from agencies without prior written agreement.