Remote Data Scientist (Part Time)

Role Overview: You will be part of a team of experienced Software Engineers (SWE Bench - Data Engineer / Data Science) contributing to benchmark-driven evaluation projects. Your main focus will be on real-world data engineering and data science workflows, involving hands-on work with production-like datasets, data pipelines, and data science tasks to enhance the performance of advanced AI systems. The ideal candidate will have a strong foundation in data engineering and data science, capable of working across data preparation, analysis, and model-related workflows within real-world codebases. Key Responsibilities: - Work with structured and unstructured datasets to support SWE Bench-style evaluation tasks. - Design, build, and validate data pipelines for benchmarking and evaluation workflows. - Perform data processing, analysis, feature preparation, and validation for data science applications. - Write, run, and modify Python code for data processing and experiment support. - Evaluate data quality, transformations, and outputs ensuring correctness and reproducibility. - Develop clean, well-documented, and reusable data workflows suitable for benchmarking. - Participate in code reviews to uphold high standards of code quality and maintainability. - Collaborate with researchers and engineers to design challenging real-world data engineering and data science tasks for AI systems. Qualifications Required: - Minimum 3+ years of experience as a Data Engineer, Data Scientist, or Software Engineer (data-focused). - Strong proficiency in Python for data engineering and data science workflows. - Demonstrable experience with data processing, analysis, and model-related workflows. - Solid understanding of machine learning and data science fundamentals. - Experience working with structured and unstructured data. - Ability to comprehend, navigate, and modify complex real-world codebases. - Experience in writing readable, reusable, maintainable, and well-documented code. - Strong problem-solving skills, including tackling algorithmic or data-intensive challenges. - Excellent spoken and written English communication skills. About Turing: Turing is a renowned research accelerator based in San Francisco, California, specializing in advancing AI labs and assisting global enterprises in deploying sophisticated AI systems. The company supports customers by accelerating frontier research with high-quality data, advanced training pipelines, and top AI researchers. Turing excels in coding, reasoning, STEM, multilinguality, multimodality, and agents. Additionally, Turing applies its expertise to aid enterprises in transforming AI concepts into proprietary intelligence, ensuring reliable performance, measurable impact, and lasting results on the P&L. Perks of Freelancing With Turing: - Work in a fully remote environment. - Opportunity to work on cutting-edge AI projects with leading LLM companies. Role Overview: You will be part of a team of experienced Software Engineers (SWE Bench - Data Engineer / Data Science) contributing to benchmark-driven evaluation projects. Your main focus will be on real-world data engineering and data science workflows, involving hands-on work with production-like datasets, data pipelines, and data science tasks to enhance the performance of advanced AI systems. The ideal candidate will have a strong foundation in data engineering and data science, capable of working across data preparation, analysis, and model-related workflows within real-world codebases. Key Responsibilities: - Work with structured and unstructured datasets to support SWE Bench-style evaluation tasks. - Design, build, and validate data pipelines for benchmarking and evaluation workflows. - Perform data processing, analysis, feature preparation, and validation for data science applications. - Write, run, and modify Python code for data processing and experiment support. - Evaluate data quality, transformations, and outputs ensuring correctness and reproducibility. - Develop clean, well-documented, and reusable data workflows suitable for benchmarking. - Participate in code reviews to uphold high standards of code quality and maintainability. - Collaborate with researchers and engineers to design challenging real-world data engineering and data science tasks for AI systems. Qualifications Required: - Minimum 3+ years of experience as a Data Engineer, Data Scientist, or Software Engineer (data-focused). - Strong proficiency in Python for data engineering and data science workflows. - Demonstrable experience with data processing, analysis, and model-related workflows. - Solid understanding of machine learning and data science fundamentals. - Experience working with structured and unstructured data. - Ability to comprehend, navigate, and modify complex real-world codebases. - Experience in writing readable, reusable, maintainable, and well-documented code. - Strong problem-solving skills, including tackling algorithmic or data-intens