Data Engineer / Data Science

Role Overview: As a Data Engineer / Data Science at our company, you will be contributing to benchmark-driven evaluation projects focused on real-world data engineering and data science workflows. Your role will involve hands-on work with production-like datasets, data pipelines, and data science tasks to help evaluate and enhance the performance of advanced AI systems. You should have a strong foundation in data engineering and data science and be able to work across data preparation, analysis, and model-related workflows in real-world codebases. Key Responsibilities: - Work with structured and unstructured datasets to support SWE Bench-style evaluation tasks. - Design, build, and validate data pipelines used in benchmarking and evaluation workflows. - Perform data processing, analysis, feature preparation, and validation for data science use cases. - Write, run, and modify Python code to process data and support experiments locally. - Evaluate data quality, transformations, and outputs for correctness and reproducibility. - Create clean, well-documented, and reusable data workflows suitable for benchmarking. - Participate in code reviews to ensure 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 overall 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 understand, navigate, and modify complex, real-world codebases. - Experience writing readable, reusable, maintainable, and well-documented code. - Strong problem-solving skills, including experience with algorithmic or data-intensive problems. - Excellent spoken and written English communication skills. Role Overview: As a Data Engineer / Data Science at our company, you will be contributing to benchmark-driven evaluation projects focused on real-world data engineering and data science workflows. Your role will involve hands-on work with production-like datasets, data pipelines, and data science tasks to help evaluate and enhance the performance of advanced AI systems. You should have a strong foundation in data engineering and data science and be able to work across data preparation, analysis, and model-related workflows in real-world codebases. Key Responsibilities: - Work with structured and unstructured datasets to support SWE Bench-style evaluation tasks. - Design, build, and validate data pipelines used in benchmarking and evaluation workflows. - Perform data processing, analysis, feature preparation, and validation for data science use cases. - Write, run, and modify Python code to process data and support experiments locally. - Evaluate data quality, transformations, and outputs for correctness and reproducibility. - Create clean, well-documented, and reusable data workflows suitable for benchmarking. - Participate in code reviews to ensure 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 overall 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 understand, navigate, and modify complex, real-world codebases. - Experience writing readable, reusable, maintainable, and well-documented code. - Strong problem-solving skills, including experience with algorithmic or data-intensive problems. - Excellent spoken and written English communication skills.