Remote Data Analyst

As a Data Analyst (MLE Bench) at Turing, your role involves contributing to benchmark-driven evaluation projects focused on real-world machine learning systems. You will be conducting hands-on analytical work with production-like datasets, metrics, and ML outputs to evaluate, diagnose, and enhance the performance of advanced AI systems. Your day-to-day responsibilities will include: - Analyzing structured and unstructured datasets generated from ML training, inference, and evaluation pipelines. - Defining, computing, and validating metrics used for evaluating model performance and behavior. - Investigating data distributions, model outputs, failure modes, and edge cases relevant to benchmark tasks. - Writing and running Python and SQL code to analyze data, create reports, and support evaluation workflows. - Validating data quality, consistency, and correctness across datasets and experiments. - Creating transparent, well-documented analytical artifacts and reproducible analysis workflows. - Collaborating with ML engineers and researchers to design challenging, real-world evaluation scenarios for MLE Bench. Qualifications required for this role include: - Minimum 3+ years of experience in data analysis and machine learning. - Comfort working at the intersection of data analysis and machine learning. - Robust analytical rigor and proficiency in working with real datasets and ML evaluation workflows. Turing, based in San Francisco, California, is the worlds leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. The company supports customers by accelerating frontier research with high-quality data, advanced training pipelines, and top AI researchers specializing in various domains. Additionally, Turing applies its expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that deliver measurable impact and drive lasting results on the P&L. As a Data Analyst (MLE Bench) at Turing, your role involves contributing to benchmark-driven evaluation projects focused on real-world machine learning systems. You will be conducting hands-on analytical work with production-like datasets, metrics, and ML outputs to evaluate, diagnose, and enhance the performance of advanced AI systems. Your day-to-day responsibilities will include: - Analyzing structured and unstructured datasets generated from ML training, inference, and evaluation pipelines. - Defining, computing, and validating metrics used for evaluating model performance and behavior. - Investigating data distributions, model outputs, failure modes, and edge cases relevant to benchmark tasks. - Writing and running Python and SQL code to analyze data, create reports, and support evaluation workflows. - Validating data quality, consistency, and correctness across datasets and experiments. - Creating transparent, well-documented analytical artifacts and reproducible analysis workflows. - Collaborating with ML engineers and researchers to design challenging, real-world evaluation scenarios for MLE Bench. Qualifications required for this role include: - Minimum 3+ years of experience in data analysis and machine learning. - Comfort working at the intersection of data analysis and machine learning. - Robust analytical rigor and proficiency in working with real datasets and ML evaluation workflows. Turing, based in San Francisco, California, is the worlds leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. The company supports customers by accelerating frontier research with high-quality data, advanced training pipelines, and top AI researchers specializing in various domains. Additionally, Turing applies its expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that deliver measurable impact and drive lasting results on the P&L.