Freelance Data Scientist – Python & SQL AI Trainer

About the role

We are looking for a freelance Data Scientist to design and deliver AI training problems for leading tech companies. The role is project‑based, remote and focuses on creating realistic, end‑to‑end data‑science challenges that test and improve AI systems.

Key responsibilities

• Design original computational data‑science problems that simulate real‑world analytical workflows across sectors such as telecom, finance, e‑commerce and healthcare.
• Create Python‑based tasks using libraries like Pandas, NumPy, SciPy, scikit‑learn, Statsmodels, Matplotlib and Seaborn.
• Ensure problems are computationally intensive, deterministic and reproducible, avoiding stochastic elements.
• Base challenges on genuine business cases (customer analytics, risk assessment, fraud detection, forecasting, optimization).
• Develop full data‑science pipelines—from data ingestion to cleaning, EDA, modeling, validation and deployment considerations.
• Incorporate big‑data processing and scalable approaches, verify solutions with Python and statistical methods, and document problem statements clearly.

Required profile

• 5+ years of hands‑on data‑science experience with measurable business impact.
• Strong portfolio of real‑world projects or publications.
• Expertise in Python programming and statistical/machine‑learning techniques.
• Proficiency with SQL for data manipulation.
• Experience with Generative AI technologies, prompt engineering and vector databases.
• Understanding of MLOps practices and model deployment workflows.
• Fluent written English (C1+).

Required skills

• Python (Pandas, NumPy, SciPy, scikit‑learn, Statsmodels, Matplotlib, Seaborn)
• SQL
• Statistical analysis and machine‑learning algorithms
• Generative AI (LLMs, Retrieval‑Augmented Generation, prompt engineering, vector databases)
• MLOps
• TensorFlow, PyTorch, LangChain

What we offer

• Project‑based freelance contracts with flexible hours (estimated 10‑20 h/week).
• Compensation up to $34 per hour, based on experience and delivery speed.
• Opportunity to work on diverse industry problems and influence AI system performance.