Data Scientist – Advanced Analytics & Machine Learning

About the role

We are looking for a Data Scientist to join a global, high‑performing team. You will design, build, and operationalize advanced analytics and machine‑learning solutions that drive customer experience, demand forecasting, operations optimization, and revenue growth across B2B and digital commerce environments.

Key responsibilities

• Design, develop and deploy predictive and prescriptive models for customer experience, demand forecasting, and operational efficiency.
• Apply machine‑learning techniques such as Gradient Boosting, Random Forest, SVM, LSTM, and Transformers to solve business problems.
• Build and maintain recommendation systems, churn prediction, propensity modeling, segmentation, and assortment optimization models.
• Perform feature engineering, clustering, statistical modeling, and time‑series analysis on structured and unstructured data.
• Transition models from notebooks to production‑ready artifacts (APIs, serialized models, containers) and integrate them via MLOps pipelines.
• Collaborate with engineering to implement CI/CD, model versioning, automated deployment, monitoring, and retraining.
• Conduct advanced statistical analysis, A/B testing, causal inference, and communicate insights to technical and non‑technical stakeholders.

Required profile

• 3+ years of hands‑on experience in applied data science and machine learning, preferably in B2B, retail or digital commerce.
• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Analytics or a related field.
• Strong proficiency in Python and its data‑science ecosystem.

Required skills

• Python
• Pandas
• NumPy
• Scikit‑learn
• Machine‑learning algorithms (Gradient Boosting, Random Forest, SVM)
• Deep‑learning frameworks (LSTM, Transformers)
• MLOps tools and practices (CI/CD, containerization, model versioning)
• Statistical analysis and time‑series modeling
• A/B testing and causal inference