About the job
We invite you to submit your CV in English, highlighting your proficiency level in the language.
Mindrift is at the forefront of connecting skilled professionals with project-based AI opportunities for renowned tech companies. Our focus is on testing, evaluating, and enhancing AI systems. Please note that participation is project-based rather than permanent employment.
Role Overview:
Each project presents unique challenges, including but not limited to:
- Crafting original computational data science problems that reflect real-world analytical workflows across sectors such as telecom, finance, government, e-commerce, and healthcare.
- Developing problems requiring proficiency in Python programming (utilizing libraries such as Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, Seaborn).
- Designing computationally intensive problems that cannot be solved manually within practical timeframes (days or weeks).
- Creating complex problems necessitating sophisticated reasoning in data processing, statistical analysis, feature engineering, predictive modeling, and extracting valuable insights.
- Formulating deterministic problems with reproducible outcomes: avoiding stochastic elements or mandating fixed random seeds for precise reproducibility.
- Grounding problems in genuine business challenges like customer analytics, risk assessment, fraud detection, forecasting, optimization, and enhancing operational efficiency.
- Structuring end-to-end problems that encompass the entire data science pipeline (data ingestion → cleaning → exploratory data analysis → modeling → validation → deployment considerations).
- Integrating scenarios that involve big data processing requiring scalable computational strategies.
- Validating solutions with Python, employing standard data science libraries and statistical techniques.
- Clearly documenting problem statements with realistic business contexts and providing verified correct answers.
What We Seek:
This opportunity is ideal for Data Science specialists with Python experience who are open to part-time, non-permanent projects. Candidates should ideally possess:
- 5+ years of relevant data science experience demonstrating tangible business impact.
- A portfolio of completed projects and publications showcasing applied problem-solving skills.
- Expertise in Python programming for data science (Pandas, Numpy, Scipy, Sklearn, Statsmodels).
- Advanced knowledge of statistical analysis and machine learning, including a deep understanding of algorithms, methods, and their practical applications.
- Strong proficiency in SQL and database operations for effective data manipulation and analysis.
- Familiarity with Generative AI technologies (e.g., LLMs, RAG, prompt engineering, vector databases).
- Knowledge of MLOps practices and model deployment workflows.
- Understanding of contemporary frameworks (e.g., TensorFlow, PyTorch, LangChain).
- Exceptional written English skills (C1+).
Application Process:
Apply → Pass qualification(s) → Join a project → Complete tasks → Get compensated.
