Data Scientist (Pricing Analytics)

Key Responsibilities

• Develop and deploy personalised pricing models using historical behaviour, purchase intent, segmentation, and contextual data.
• Apply advanced statistical and machine learning techniques to estimate demand curves and user-level price sensitivity.
• Design and execute pricing A/B tests, analyzing lift, revenue impact, and user experience trade-offs.
• Develop dynamic pricing frameworks that adjust in real-time based on inputs such as location, time, inventory, and user cohorts.
• Collaborate with engineering teams to integrate models into pricing engines and user-facing platforms.
• Communicate findings clearly to business stakeholders and make data-backed pricing recommendations.

Must-Have Qualifications

• 36 years of experience in data science, pricing, or quantitative strategy roles.
• Strong programming skills in Python and SQL; experience with libraries like scikit-learn, stats models, or XGBoost.
• Deep knowledge of pricing analytics, revenue management, and behavioral economics.
• Experience in building predictive models for conversion, elasticity, or revenue uplift.
• Ability to synthesize complex data into actionable strategies with business impact.
• Strong experimentation mindset with familiarity in causal inference and A/B testing methodologies.