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Data Scientist Specialist - Freelance AI Trainer Project

Roles & Responsibilities

  • 2+ years of hands-on experience building and deploying data science or machine learning models in production.
  • Proficiency in Python and ML/data libraries (Pandas, NumPy, scikit-learn, PyTorch or similar).
  • Experience with large-scale datasets and distributed tools such as Spark; comfortable with cloud environments (GCP or AWS).
  • Strong ability to communicate with both technical and non-technical stakeholders and translate requirements into actionable results.

Requirements:

  • Design, train, and evaluate end-to-end models from exploratory analysis through production deployment.
  • Collaborate with software engineers, analysts, and data scientists to deploy scalable, production-ready models in dynamic environments.
  • Translate ambiguous problems into actionable recommendations for stakeholders and communicate results effectively.
  • Explore and validate large, diverse datasets using Pandas, NumPy, and Spark to inform model design and drive performance improvements; stay current with advances in statistics, ML, and data engineering.

Job description

Data Scientist Specialist

What You’ll Do

You’ll design and implement data science and machine learning solutions that blend cutting-edge research with practical deployment. Working across industries, domains, and use cases, you’ll tackle challenging analytical problems, build robust models, and deliver insights that power client-facing tools and internal platforms.

  • Develop End-to-End Models: Design, train, and evaluate models for prediction, classification, optimization, or inference—taking projects from exploratory analysis through production deployment.
  • Collaborate on Real-World Solutions: Partner with software engineers, analysts, and fellow data scientists to integrate data-driven models into scalable, deployable systems that operate in dynamic production environments.
  • Client-Focused Problem Solving: Work closely with stakeholders to frame ambiguous problems, explore solution paths, and translate complex technical insights into clear, actionable recommendations.
  • Explore, Iterate, Validate: Lead the exploration and analysis of large and diverse datasets using tools like Pandas, NumPy, and Spark to inform model design, evaluate performance, and identify opportunities for improvement.
  • Research-Driven Innovation: Stay current with advances in statistics, machine learning, and data engineering practices—adapting new methods and technologies to deliver measurable impact on real-world problems.

What We Need

Professional Experience

  • 2+ years of hands-on experience building and deploying data science or machine learning models in production environments.
  • Proven ability to take models from prototype to production using Python-based workflows.
  • Experience engaging with technical and non-technical stakeholders to refine requirements and communicate results effectively.

Technical Expertise

  • Strong proficiency in Python and commonly used ML/data libraries (Pandas, NumPy, scikit-learn, PyTorch, or similar).
  • Experience working with large-scale datasets and distributed tools such as Spark.
  • Comfort navigating cloud environments (e.g., GCP, AWS, or similar); Databricks experience is a plus.
  • Solid understanding of statistical modeling, experimental design, model evaluation, and data debugging practices.
  • Strong code hygiene — able to write clean, modular, and testable code in collaborative, version-controlled environments.

 

We offer a pay range of $30+ per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor you’ll supply a secure computer and high‑speed internet; company‑sponsored benefits such as health insurance and PTO do not apply.

Important:

All candidates must pass an interview as part of the contracting process.

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