Remote Data Scientist (Python & SQL) - Freelance AI Trainer

Bilinguallink; Vaughan; Remote; CAD 79,000 - 108,000; Part time

Job summary

AtMindrift is seeking a Data Science AI Trainer to join our remote freelance team. You will design real-world computational DS problems, create Python-based tasks, and validate solutions across industries, leveraging GenAI and ML techniques.

The role requires at least 5 years of hands-on experience, a strong portfolio, and advanced English. This is a remote, freelance, part-time opportunity with flexible scheduling for global projects.

Qualifications

• Master’s or PhD in a quantitative field such as DS, statistics, math or CS.
• At least 5 years of hands-on data science experience with demonstrated impact.
• Strong portfolio of projects and publications showing real-world problem solving.
• Proficiency in Python for data science (pandas, numpy, scipy, scikit-learn, statsmodels).
• Deep knowledge of statistical analysis and ML methods with practical apps.
• SQL and database operations for data manipulation and analysis.
• Experience with GenAI technologies (LLMs, RAG, prompt engineering).
• Knowledge of MLOps and model deployment workflows.
• Familiarity with TensorFlow, PyTorch, LangChain.
• Advanced English proficiency (C1+).

Responsibilities

• Design computational data science problems simulating real-world workflows.
• Create Python-based tasks using pandas, numpy, scipy, and scikit-learn.
• Ensure problems are computationally intensive with reproducible answers.
• Develop scenarios involving data processing, modeling, and insight extraction.
• Cover end-to-end DS pipelines: ingesting, cleaning, EDA, modeling, validation.
• Collaborate on GenAI projects and scalable data-processing challenges.
• Provide clear problem statements with realistic business contexts.
• Verify solutions and provide verified correct answers.

Skills

Python (Data Science)

SQL

GenAI knowledge

ML/Statistical modeling

MLOps

TensorFlow/PyTorch

LangChain

English Proficiency (C1+)

Education

Master’s degree

PhD degree

Tools

Pandas

NumPy

SciPy

scikit-learn

Statsmodels

Matplotlib/Seaborn

Job description

This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.

AtMindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.

What we do

The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.

About the Role

GenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.

Although every project is unique, you might typically:

• Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).
• Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).
• Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).
• 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: avoid stochastic elements or require fixed random seeds for exact reproducibility.
• Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
• Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → 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.

Compensation

On this project, contributors can earn up to$55 per hour equivalent, depending on their level and pace of contribution.

Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

• You hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field.
• You have at least 5 years of hands‑on data science experience with proven business impact.
• You have portfolio of completed projects and publications showcasing real-world problem-solving.
• You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels).
• You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications.
• You are proficient in SQL and database operations for data manipulation and analysis.
• You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).
• You have good understanding of MLOps practices and model deployment workflows.
• You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).
• Your level of English is advanced (C1) or above.

• You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.
• Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.

Why this freelance opportunity might be a great fit for you?

• Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.
• Work on advanced AI projects and gain valuable experience that enhances your portfolio.
• Influence how future AI models understand and communicate in your field of expertise.