About the job
We invite you to submit your CV in English, along with your English proficiency level.
At Mindrift, we bridge the gap between specialists and project-based AI opportunities offered by leading technology companies, with a focus on evaluating, testing, and enhancing AI systems. Please note, this role is project-based and does not involve permanent employment.
Opportunity Highlights:
Each project entails distinct tasks, and contributors may:
- Craft innovative computational data science problems that mirror real-world analytical workflows across sectors such as telecom, finance, government, e-commerce, and healthcare.
- Develop challenges requiring Python solutions utilizing libraries like Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, and Seaborn.
- Ensure that problems are computationally demanding and cannot be manually resolved within a reasonable timeframe (days/weeks).
- Formulate problems that necessitate complex reasoning chains in areas like data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.
- Produce deterministic problems with reproducible outcomes, avoiding stochastic elements unless fixed random seeds are provided for exact replication.
- Base problems on actual business challenges, including customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
- Design comprehensive problems that encompass the entire data science pipeline (data ingestion → cleaning → exploratory data analysis → modeling → validation → deployment considerations).
- Integrate big data processing scenarios that require scalable computational techniques.
- Validate solutions utilizing Python alongside standard data science libraries and statistical approaches.
- Clearly document problem statements within realistic business contexts and provide verified correct answers.
What We Are Looking For:
This opportunity suits Data Science specialists with expertise in Python who are open to part-time, non-permanent projects. Ideally, candidates will possess:
- 5+ years of hands-on data science experience demonstrating tangible business impact.
- A portfolio of completed projects and publications that showcase real-world problem-solving capabilities.
- Proficiency in Python programming for data science (Pandas, Numpy, Scipy, Scikit-learn, Statsmodels).
- Advanced skills in statistical analysis and machine learning, with a deep understanding of algorithms, methods, and their practical applications.
- Expertise in SQL and database operations for data manipulation and analysis.
- Experience with Generative AI technologies (LLMs, RAG, prompt engineering, vector databases).
- Familiarity with MLOps practices and model deployment workflows.
- Knowledge of modern frameworks such as TensorFlow, PyTorch, and LangChain.
- Exceptional written English skills (C1+).
How the Process Works:
Apply → Pass qualifications → Join a project → Complete tasks → Get compensated.
