Freelance Data Science Engineer (Python & SQL)

Participation is project-based, not permanent employment.

What This Opportunity Involves

• Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare)

• Create problems requiring Python programming to solve (using Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, Seaborn)

• Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks)

• Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction

• Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility

• Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency

• Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations)

• Incorporate big data processing scenarios requiring scalable computational approaches

• Verify solutions using Python with standard data science libraries and statistical methods

• Document problem statements clearly with realistic business contexts and provide verified correct answers

What We Look For

• 5+ years of hands‑on data science experience with proven business impact

• Portfolio of completed projects and publications showcasing real‑world problem‑solving

• Expert Python programming for data science (pandas, numpy, scipy, scikit‑learn, statsmodels)

• Expert statistical analysis and machine learning – deep understanding of algorithms, methods, and their practical applications

• Expert with SQL and database operations for data manipulation and analysis

• Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases)

• Understanding of MLOps practices and model deployment workflows

• Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain)

• Strong written English (C1+)

How It Works

Apply, Pass qualification(s), Join a project, Complete tasks, Get paid.

Project time expectations

For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.