About the job
We kindly request that you submit your CV in English and specify your English proficiency level.
Mindrift connects professionals with exciting project-based AI opportunities for leading tech companies, focusing on the assessment, testing, and enhancement of AI systems. Please note that participation is project-based and does not guarantee permanent employment.
Opportunity Overview
While each project presents unique challenges, contributors may be involved in tasks such as:
- Creating original computational data science problems that emulate real-world analytical workflows across various sectors (telecommunications, finance, government, e-commerce, healthcare).
- Formulating problems that require Python programming for resolution (utilizing libraries such as Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, Seaborn).
- Ensuring that the problems are computationally demanding and cannot be solved manually within a reasonable timeframe (days/weeks).
- Developing challenges that necessitate complex reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.
- Designing deterministic problems with reproducible answers, avoiding stochastic elements or requiring fixed random seeds for exact reproducibility.
- Grounding problems in actual business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
- Crafting end-to-end problems that cover the entire data science pipeline (data ingestion → cleaning → exploratory data analysis → modeling → validation → deployment considerations).
- Incorporating big data processing scenarios that require scalable computational approaches.
- Validating solutions using Python with standard data science libraries and statistical methodologies.
- Documenting problem statements clearly with realistic business contexts and providing verified correct answers.
What We Seek
This opportunity is ideal for Data Science specialists with Python expertise who are open to part-time, non-permanent projects. The perfect candidates will possess:
- 5+ years of practical data science experience demonstrating tangible business impact.
- A portfolio of completed projects and publications showcasing effective problem-solving skills.
- Proficiency in Python for data science (including Pandas, Numpy, Scipy, Sklearn, Statsmodels).
- Advanced statistical analysis and machine learning expertise, with a solid understanding of algorithms, methods, and their practical applications.
- Strong SQL skills for data manipulation and analysis.
- Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).
- A grasp of MLOps practices and model deployment workflows.
- Familiarity with modern frameworks (TensorFlow, PyTorch, LangChain).
- Exceptional written English skills (C1+ level).
Process
Apply → Pass qualifications → Join a project → Complete tasks → Receive payment
