About the job
We invite you to submit your CV in English and specify your level of English proficiency.
At Mindrift, we specialize in connecting skilled professionals with project-based AI opportunities from top technology companies, emphasizing the testing, evaluation, and enhancement of AI systems. This role involves project-specific engagement, rather than permanent employment.
Role Overview:
Each project presents distinct tasks, where contributors may be responsible for:
- Crafting original computational data science challenges that replicate real-world analytical workflows across various sectors such as telecom, finance, government, e-commerce, and healthcare.
- Formulating problems that necessitate Python coding to resolve, utilizing libraries like Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, and Seaborn.
- Ensuring that these problems are computationally demanding, requiring extensive processing time that cannot be resolved manually within practical timeframes.
- Developing scenarios that involve complex reasoning in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.
- Designing deterministic problems with reproducible solutions, avoiding stochastic components or ensuring fixed random seeds for exact replication.
- Creating challenges based on genuine business problems, including customer analytics, risk assessment, fraud detection, forecasting, optimization, and enhancing operational efficiency.
- Structuring end-to-end problems that cover the entire data science pipeline (data ingestion → cleaning → exploratory data analysis → modeling → validation → deployment considerations).
- Integrating big data processing situations that demand scalable computational methods.
- Validating solutions using Python alongside standard data science libraries and statistical techniques.
- Clearly documenting problem statements with realistic business contexts and providing verified correct answers.
Who We Are Looking For:
This opportunity aligns well with Data Science experts experienced in Python who are available for part-time, non-permanent projects. Ideally, candidates will possess:
- A minimum of 5 years of hands-on experience in data science with demonstrated business impact.
- A portfolio of completed projects and publications that highlight real-world problem-solving capabilities.
- Proficient Python programming skills for data science (pandas, numpy, scipy, scikit-learn, statsmodels).
- A deep understanding of statistical analysis and machine learning, including algorithms, methodologies, and practical applications.
- Expertise in SQL and database management for data manipulation and analysis.
- Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).
- Familiarity with MLOps practices and model deployment workflows.
- Knowledge of contemporary frameworks (TensorFlow, PyTorch, LangChain).
- Strong written English skills (C1 or higher).
Application Process:
Apply → Pass qualifications → Join a project → Complete tasks → Get paid
