Freelance Data Science Engineer (Python & SQL)

58 USD/ godz.
SeniorPart-time
#342977·Dodano dziś·0
Źródło: Mindrift
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Tech Stack / Keywords

Data SciencePythonSQLAITestingPandasNumPyBig Data

Firma i stanowisko

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.


Wymagania

  • 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 with deep understanding of algorithms, methods, and 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+)

Obowiązki

  • 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

Oferta

  • Project-based participation, not permanent employment
  • Estimated 10–20 hours per week during active phases
  • Compensation up to $58 per hour equivalent depending on level and pace of contribution

Inne informacje

  • Please submit your CV in English and indicate your level of English proficiency
  • Participation is project-based, not permanent employment
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