Scientifically Grounded Data Scientist

Role Overview

Deliver measurable commercial and operational impact through operations intelligence, customer intelligence, and personalization. Contribute to the development of the Decision Science roadmap for operations intelligence and customer intelligence.

What You Will Do

Develop models for demand forecasting, inventory and replenishment optimization, assortment and allocation, supply chain and logistics optimization, workforce and store capacity planning, and pricing and markdown optimization. Build predictive, prescriptive, and optimization models to improve business performance and operational efficiency.

Why It Might Be a Fit

You will work closely with business stakeholders, product managers, data engineers, and analytics teams to translate business challenges into scalable AI products that are deployed on Google Cloud Platform (GCP).

Requirements

• Master’s degree (MSc) or PhD from an established, internationally recognized university in Mathematics, Statistics, Physics, Computer Science, Data Science, Operations Research, or a closely related quantitative field.
• Approximately 4–5 years of relevant professional experience after graduation in data science, statistical modeling, applied mathematics, or machine learning.
• A strong foundation in probability theory, statistical inference, linear algebra, numerical methods, and mathematical optimization, with the ability to explain the assumptions and limitations of different models.
• Practical experience in developing and validating predictive and optimization models; experience in operations intelligence (forecasting, inventory, supply chain, and pricing) or customer intelligence (recommendation systems, personalization, and CRM analytics) is an advantage.
• Excellent programming skills in Python and SQL, with experience processing large-scale structured and unstructured datasets.
• Experience with scientific Python libraries (e.g., NumPy, SciPy, statsmodels, and scikit-learn) and ML frameworks such as XGBoost, LightGBM, TensorFlow, or PyTorch.
• Familiarity with Google Cloud Platform (GCP), including BigQuery, Vertex AI, and modern MLOps practices, is an advantage.
• Understanding of modern AI methods, including deep learning and Generative AI / LLMs, and the judgment to identify when these approaches are—or are not—appropriate.

Benefits

• Job in a dynamic and innovative environment
• Collaborative and diverse team
• Benefits package