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Freelance Data Scientist (Python & SQL) - AI Project Specialist

toloka-aiRemote — Manitoba, CanadaNew
Remote Contract CA$55/hr - CA$55/hr

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Experience Level

Experience

Qualifications

Ideal Candidate Profile:This opportunity suits Data Science specialists with extensive experience in Python who are flexible to engage in part-time, non-permanent projects. Desired qualifications include:5+ years of practical data science experience with demonstrable business impact. A portfolio showcasing completed projects and publications that highlight real-world problem-solving capabilities. Proficient in Python for data science (including pandas, numpy, scipy, scikit-learn, statsmodels). Advanced skills in statistical analysis and machine learning, with a thorough understanding of algorithms, methodologies, and their real-world applications. Expertise in SQL and database operations for effective data manipulation and analysis. Familiarity with GenAI technologies (such as LLMs, RAG, prompt engineering, vector databases). Knowledge of MLOps practices and model deployment workflows. Understanding of contemporary frameworks (TensorFlow, PyTorch, LangChain). Strong command of written English (C1+ level).

About the job

Please submit your CV in English, specifying your English proficiency level.

At Mindrift, we link talented specialists with project-based AI opportunities within renowned tech companies, concentrating on the assessment, testing, and enhancement of AI systems. This role is project-based rather than a permanent position.

Opportunity Overview:

Each project presents unique challenges, but contributors may be tasked with:

  • Crafting original computational data science challenges that mimic real-world analytical workflows across various domains including telecom, finance, government, e-commerce, and healthcare.
  • Implementing Python programming solutions for these challenges (utilizing libraries such as Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, Seaborn).
  • Ensuring tasks are computationally demanding and not solvable manually within typical timeframes (days/weeks).
  • Developing challenges that necessitate complex reasoning in data processing, statistical analysis, feature engineering, predictive modeling, and deriving insights.
  • Creating deterministic problems with consistent outputs: avoiding stochastic elements or mandating fixed random seeds for exact reproducibility.
  • Grounding problems in authentic business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
  • Designing comprehensive problems that cover the entire data science pipeline (data ingestion → cleaning → exploratory data analysis → modeling → validation → deployment considerations).
  • Incorporating big data challenges that necessitate scalable computational strategies.
  • Validating solutions through Python and standard data science libraries along with statistical techniques.
  • Clearly documenting problem statements with realistic business contexts and providing verified correct answers.

About toloka-ai

Mindrift is dedicated to connecting talented specialists with innovative project-based AI opportunities in leading tech companies, focusing on the evaluation and enhancement of AI systems.

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