Public summary
Seeking a freelance Data Science Engineer for project-based AI opportunities with leading tech companies. The role involves designing and solving complex data science problems using Python and SQL, focusing on real-world business challenges across various industries. Work is part-time and non-permanent, with tasks requiring around 10–20 hours per week when projects are active. Compensation up to $58 per hour, dependent on contribution level and project scope. Strong English proficiency (C1+) required. Applicants must submit CVs in English and demonstrate relevant data science and machine learning expertise.
Location and work setup
- Location
- Frankfurt
- Remote status
- Remote
- German requirement signal
- No German Required Detected
- Detected job language
- English
Salary
USD 58.00 - 58.00 hour
Responsibilities
Design original computational data science problems simulating real-world analytical workflows; develop problems requiring Python programming and non-trivial reasoning in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction; create deterministic problems with reproducible answers; base problems on real business challenges across industries such as telecom, finance, government, e-commerce, and healthcare; design end-to-end data science pipelines including data ingestion, cleaning, exploratory data analysis, modeling, validation, and deployment considerations; incorporate big data processing scenarios requiring scalable computational approaches; verify solutions using Python and standard data science libraries; document problem statements clearly with realistic business contexts and provide verified correct answers.
Qualifications
At least 5 years of hands-on data science experience with proven business impact; portfolio of completed projects and publications showcasing real-world problem-solving; expert proficiency in Python programming for data science (including pandas, numpy, scipy, scikit-learn, statsmodels); expert knowledge of statistical analysis and machine learning algorithms and their practical applications; expertise in SQL and database operations for data manipulation and analysis; experience with generative AI technologies including large language models, retrieval-augmented generation, prompt engineering, and vector databases; understanding of MLOps practices and model deployment workflows; familiarity with modern machine learning frameworks such as TensorFlow, PyTorch, and LangChain; strong written English skills (C1+).