About the job
Please submit your CV in English and specify your English proficiency level.
At Mindrift, we bridge the gap between talented specialists and exciting project-based AI opportunities with leading technology companies. Our focus is on the testing, evaluation, and enhancement of AI systems. Note: Participation is project-based and not a permanent employment position.
Role Overview
As a freelance Data Science Engineer, you will tackle a variety of unique projects. Your responsibilities may include:
- Designing original computational data science challenges that replicate real-world analytical processes across various sectors such as telecommunications, finance, government, e-commerce, and healthcare.
- Formulating problems that necessitate Python programming for resolution, utilizing libraries like Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, and Seaborn.
- Ensuring tasks are computationally demanding, with solutions that cannot be feasibly achieved manually within a short timeframe (days/weeks).
- Creating problems that involve complex reasoning chains in data manipulation, statistical analysis, feature engineering, predictive modeling, and deriving insights.
- Developing deterministic problems with reproducible outcomes, minimizing stochastic elements or requiring fixed random seeds for exact results.
- Crafting scenarios based on actual business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and improving operational efficiency.
- Designing comprehensive problems that encompass the entire data science pipeline (data ingestion → cleaning → exploratory data analysis → modeling → validation → deployment considerations).
- Addressing big data processing challenges that necessitate scalable computational strategies.
- Validating solutions using Python and standard data science libraries along with statistical techniques.
- Clearly documenting problem statements in a business context and providing verified correct answers.
Candidate Profile
This role is ideal for Data Science professionals with extensive experience in Python, seeking part-time, non-permanent project work. The ideal candidates should possess:
- A minimum of 5 years of practical data science experience demonstrating measurable business impact.
- A portfolio showcasing completed projects and publications that highlight real-world problem-solving capabilities.
- Proficient Python programming skills for data science (including pandas, numpy, scipy, scikit-learn, and statsmodels).
- Expertise in statistical analysis and machine learning, with a deep understanding of algorithms, methods, and their practical applications.
- Command of SQL and database operations for effective data manipulation and analysis.
- Familiarity with GenAI technologies, including LLMs, RAG, prompt engineering, and vector databases.
- Insight into MLOps practices and model deployment workflows.
- Knowledge of modern frameworks, such as TensorFlow, PyTorch, and LangChain.
- Strong written English communication skills (C1+ level).
Application Process
Apply → Complete qualifications → Join a project → Undertake tasks → Receive payment
