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Freelance Data Science Engineer - Python & SQL (Remote)

toloka-aiRemote — Stuttgart, Baden-Württemberg, Germany
Remote Contract $58/hr - $58/hr

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Experience Level

Experience

Qualifications

QualificationsThis opportunity is suited for data science specialists experienced in Python, looking for part-time, non-permanent project work. Ideal candidates will possess:A minimum of 5 years of practical experience in data science with a demonstrated impact on business outcomes. A portfolio showcasing completed projects and publications that illustrate real-world problem-solving capabilities. Proficiency in Python programming for data science, including libraries such as Pandas, Numpy, Scipy, Scikit-learn, and Statsmodels. A deep understanding of statistical analysis and machine learning, with expertise in relevant algorithms and their applications. Strong SQL skills for data manipulation and analysis. Familiarity with GenAI technologies (e.g., LLMs, RAG, prompt engineering, vector databases). An understanding of MLOps practices and model deployment workflows. Knowledge of contemporary frameworks, including TensorFlow, PyTorch, and LangChain. Exceptional written English skills (C1+).

About the job

Please submit your CV in English and indicate your English proficiency level.

toloka-ai, working with Mindrift, connects data science professionals to project-based contract work in AI. Assignments support technology companies as they develop, test, and evaluate AI systems. This is not a permanent employment role; work is structured around specific projects.

Role overview

  • Design computational data science problems that mirror analytics workflows in industries such as telecom, finance, government, e-commerce, and healthcare.
  • Create problems requiring Python programming, using libraries like Pandas, Numpy, Scipy, Scikit-learn, Statsmodels, Matplotlib, and Seaborn.
  • Ensure challenges are computationally intensive, with solutions that would take significant manual effort.
  • Develop scenarios involving complex data processing, statistical analysis, feature engineering, predictive modeling, and extracting insights.
  • Write deterministic problems with reproducible outcomes by avoiding randomness or using fixed seeds.
  • Base challenges on real business needs such as customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
  • Design end-to-end data science tasks covering data ingestion, cleaning, exploratory analysis, modeling, validation, and deployment considerations.
  • Include big data scenarios that require scalable computational solutions.
  • Validate solutions in Python using standard data science libraries and statistical techniques.
  • Document each problem clearly, provide realistic business context, and supply verified correct answers.

Requirements

  • Minimum 5 years of hands-on data science experience with demonstrated business impact.
  • Portfolio of completed projects or publications showing practical problem-solving.
  • Advanced Python programming for data science, including Pandas, Numpy, Scipy, Scikit-learn, and Statsmodels.
  • Strong background in statistical analysis and machine learning, with knowledge of key algorithms and applications.
  • Solid SQL skills for data manipulation and analysis.
  • Familiarity with GenAI tools and concepts (LLMs, RAG, prompt engineering, vector databases).
  • Understanding of MLOps and model deployment workflows.
  • Experience with frameworks such as TensorFlow, PyTorch, and LangChain.
  • Excellent written English (C1+ level).

Application process

  1. Apply
  2. Pass qualifications
  3. Join a project
  4. Complete tasks
  5. Receive compensation

This freelance, remote position is open to candidates based in Stuttgart, Baden-Württemberg, Germany, as well as those working remotely.

About toloka-ai

Mindrift specializes in connecting skilled professionals with dynamic project-based opportunities in artificial intelligence. By collaborating with top tech companies, we focus on testing, evaluating, and improving AI systems, ensuring a robust approach to artificial intelligence development.

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