Data Scientist (Python & SQL) - Freelance AI Trainer

About the Role

The role entails working on a project-by-project basis, with each project presenting unique tasks and challenges. You will be expected to develop problems that require non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Your expertise in Python and SQL will be essential in creating deterministic problems with reproducible answers.

What You Will Do

• Design original computational data science problems that simulate real-world analytical workflows across industries such as telecom, finance, government, e-commerce, and healthcare
• Create problems requiring Python programming to solve using libraries such as Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, and Seaborn
• Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes
• Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction
• Create deterministic problems with reproducible answers, avoiding stochastic elements or requiring fixed random seeds for exact reproducibility
• Base problems on real business challenges such as customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency
• Design end-to-end problems spanning the complete data science pipeline, including data ingestion, cleaning, EDA, modeling, validation, and deployment considerations
• Incorporate big data processing scenarios requiring scalable computational approaches
• Verify solutions using Python with standard data science libraries and statistical methods
• Document problem statements clearly with realistic business contexts and provide verified correct answers

What We Are Looking For

• 5+ years of hands-on data science experience with proven business impact
• Portfolio of completed projects and publications showcasing real-world problem-solving
• Expert Python programming for data science using libraries such as Pandas, Numpy, Scipy, Scikit-learn, and Statsmodels
• Expert statistical analysis and machine learning
• Deep understanding of algorithms, methods, and their practical applications
• Expertise in SQL and database operations for data manipulation and analysis
• Experience with GenAI technologies such as LLMs, RAG, prompt engineering, and vector databases
• Understanding of MLOps practices and model deployment workflows
• Knowledge of modern frameworks such as TensorFlow, PyTorch, and LangChain
• Strong written English (C1+)

Nice to Have

• Experience working with cloud-based data platforms and big data technologies
• Familiarity with agile development methodologies and version control systems such as Git
• Knowledge of data visualization tools such as Tableau or Power BI
• Certification in data science or a related field

Benefits and Perks

• Competitive hourly rate equivalent to up to $55 per hour
• Flexible, remote work arrangement with the opportunity to work on high-impact projects
• Access to a network of leading tech companies and data science professionals
• Opportunities for professional growth and development in the field of AI and data science
• Flexible project schedule with estimated 10-20 hours of work per week during active phases
• Potential for long-term collaboration and repeat projects
• Opportunity to work on a wide range of projects and industries, expanding your portfolio and skillset

• Tip: Showcase your portfolio and demonstrate your expertise in data science and machine learning to stand out in the application process.
• Tip: Familiarize yourself with the latest tools and technologies in the field, such as GenAI and MLOps, to increase your competitiveness.
• Tip: Highlight your experience working with Python and SQL, and be prepared to provide examples of your programming skills.
• Tip: Research the company and the types of projects they work on to demonstrate your understanding of the role and the industry.
• Tip: Be prepared to discuss your experience working on freelance or contract projects, and how you manage your time and prioritize tasks in a remote work environment.
• Tip: Consider highlighting any experience you have working with big data, cloud-based platforms, or data visualization tools to demonstrate your versatility and range of skills.
• Tip: Prepare to discuss your understanding of algorithms, methods, and their practical applications, and be ready to provide examples of how you have applied these concepts in your work.