As part of our Data Science unit, you will sit directly with the Pricing team, using your expertise to advance and refine our pricing engine. Your main task will be to design, build, and continuously improve sales and demand forecasts that deliver critical insights for pricing decisions. While your day-to-day work is closely aligned with business stakeholders, you will be supported by—and contribute to—a broader community of data scientists and engineers.

Your Responsibilities:

• Design, build, validate, deploy, and monitor machine learning models that power pricing decisions (utilizing tools such as scikit-learn, PyMC, pytorch-forecasting, CausalML, XGBoost, LightGBM).
• Run experiments and build prototypes to innovate on pricing, especially in sales forecasting
• Actively participate in discoveries and discussions with the pricing and data team to improve our pricing solutions.
• Conduct causal analyses and A/B tests to quantify impact on revenue, margin, and conversion, and define success metrics.
• Build robust data pipelines (using dbt) and features from pricing-specific data to productionize automated solutions.

Your Qualifications:

• Several years of professional experience in the end-to-end development of Data Science projects from ideation to operations. Experience in the eCommerce sector with a focus on pricing, sales and demand forecasting, or similar is a plus.
• A master’s degree or higher in a quantitative field, such as statistics, computer science, mathematics, engineering, or economics.
• Proficient in SQL and Python, and possess strong data science fundamentals, including modeling, data structures, and visualization techniques.
• Knowledge of software development and related tools (e.g., Git, Docker, Azure, AWS).
• A problem-solving, hands-on, and analytical personality, with a solution-oriented and initiative-taking mindset.
• Excellent English communication skills.