Back
Mid-level Data Scientist title, metro location, and broadly applicable ML/analytics skills drive high applicant competition.
Core ML skills transfer across industries, but retail/e-commerce domain experience and CV/LLM exposure increase fit sensitivity.
Explicit 4–8 years plus required Python, SQL, Spark and production ML experience yields medium shortlisting strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design and deployment of ML/analytics solutions targeting retail and e-commerce challenges like forecasting, segmentation, churn, and personalization.
Translate business needs into ML problem statements, build end-to-end scalable modeling pipelines (Spark/PySpark preferred), and ensure model reliability with rigorous evaluation and monitoring.
Work hands-on with advanced AI techniques including Computer Vision and Generative AI/LLMs for use cases such as product search and customer support, while driving technical standards and documentation.
4-8 years of experience in data science, applied ML, or advanced analytics with demonstrable production impact.
Bachelor’s or Master’s degree (or equivalent) in Data Science, Computer Science, Statistics, Mathematics, or related field.
Strong programming skills in Python (including Pandas, NumPy, Scikit-learn) and solid SQL proficiency.
Experience with large-scale data handling and Spark/PySpark; strong foundational knowledge in classical ML, feature engineering, and model evaluation.
Experienced in operationalizing ML solutions end-to-end in retail/e-commerce domains, focusing on demand forecasting, pricing, promo, inventory, or customer lifecycle analytics.
Able to work collaboratively with engineering and platform teams to integrate, monitor, and retrain models, leveraging MLOps principles and cloud platforms (Azure preferred).
Comfortable applying cutting-edge AI technologies (Generative AI, Computer Vision) specifically to solve retail use cases and drive business decisions through data storytelling.