About this role
AutoRoboto is seeking a Data Analyst to join our engineering team in Mountain View, CA. This role will work with complex product, operational, automation, robotics, and testing-related datasets to help the company evaluate operational systems and make data-driven decisions. The Data Analyst will collect, validate, and analyze operational data; apply quantitative and statistical methods to define operational problems and evaluate alternatives; develop and test analytical models and decision-support workflows; create reports and dashboards; and collaborate with engineering to support analytical tools, automation workflows, and operational improvements.
The ideal candidate has a strong quantitative background, programming experience, and the ability to translate complex operational data into clear, actionable insights for technical and business stakeholders.
• Collect, query, clean, validate, and structure raw data from internal systems, product and operational data sources, authorized testing workflows, automation tools, and robotics-based data collection processes for downstream analysis, reporting, and modeling. • Assess data quality, completeness, consistency, and accuracy; identify anomalies, missing values, and data integrity issues; and recommend practical approaches for improving the reliability of operational data collection. • Perform exploratory, statistical, and operations analysis to identify trends, constraints, correlations, patterns, outliers, and drivers of key operational, product, or business metrics. • Develop, test, and refine quantitative models, analytical algorithms, and decision-support methods using Python, SQL, and statistical/data modeling techniques. • Evaluate model performance and alternative operational approaches using appropriate quantitative metrics; document assumptions, limitations, and expected operational impact. • Collaborate with the engineering team to support analytical prototypes, define data requirements, validate feature logic, test model outputs, and assist with production-ready analytical, automation, and data collection workflows. • Build reports, dashboards, charts, and visualizations to communicate findings clearly to engineering, product, operations, and business teams. • Translate analytical findings into actionable recommendations for operational, product, and business improvements, including improvements to data collection, automation, testing, and robotics workflows. • Prepare written summaries and presentations explaining methodology, findings, risks, operational tradeoffs, and recommended next steps.
• Bachelor’s degree, or foreign equivalent, in Operations Research, Statistics, Mathematics, Computer Science, Data Science, Engineering, Business Analytics, or a closely related quantitative field . • 2 years of experience in quantitative analytics, operations analysis, data analysis, data modeling, business analytics, product analytics, or a related analytical role. Additional related experience is preferred but not required. • Experience using Python and SQL to query, clean, transform, analyze, and model data. • Knowledge of statistical analysis, operations analysis, data modeling, data quality assessment, exploratory data analysis, and quantitative problem-solving methods. • Experience creating reports, dashboards, charts, or visualizations using Tableau or similar business intelligence / visualization tools. • Ability to communicate technical findings, operational tradeoffs, and recommendations clearly to both technical and non-technical stakeholders. • Strong attention to detail, analytical judgment, and problem-solving ability.
• Experience or familiarity with big data or distributed data tools such as Spark, Hadoop, Cassandra, or similar technologies. • Experience working with engineering teams on data pipelines, analytical prototypes, model validation, automation workflows, robotics workflows, or production data workflows. • Experience analyzing product, operational, SaaS, automation, robotics, logistics, authorized penetration-testing, or security-assessment datasets.
The ideal candidate has a strong quantitative background, programming experience, and the ability to translate complex operational data into clear, actionable insights for technical and business stakeholders.
• Collect, query, clean, validate, and structure raw data from internal systems, product and operational data sources, authorized testing workflows, automation tools, and robotics-based data collection processes for downstream analysis, reporting, and modeling. • Assess data quality, completeness, consistency, and accuracy; identify anomalies, missing values, and data integrity issues; and recommend practical approaches for improving the reliability of operational data collection. • Perform exploratory, statistical, and operations analysis to identify trends, constraints, correlations, patterns, outliers, and drivers of key operational, product, or business metrics. • Develop, test, and refine quantitative models, analytical algorithms, and decision-support methods using Python, SQL, and statistical/data modeling techniques. • Evaluate model performance and alternative operational approaches using appropriate quantitative metrics; document assumptions, limitations, and expected operational impact. • Collaborate with the engineering team to support analytical prototypes, define data requirements, validate feature logic, test model outputs, and assist with production-ready analytical, automation, and data collection workflows. • Build reports, dashboards, charts, and visualizations to communicate findings clearly to engineering, product, operations, and business teams. • Translate analytical findings into actionable recommendations for operational, product, and business improvements, including improvements to data collection, automation, testing, and robotics workflows. • Prepare written summaries and presentations explaining methodology, findings, risks, operational tradeoffs, and recommended next steps.
• Bachelor’s degree, or foreign equivalent, in Operations Research, Statistics, Mathematics, Computer Science, Data Science, Engineering, Business Analytics, or a closely related quantitative field . • 2 years of experience in quantitative analytics, operations analysis, data analysis, data modeling, business analytics, product analytics, or a related analytical role. Additional related experience is preferred but not required. • Experience using Python and SQL to query, clean, transform, analyze, and model data. • Knowledge of statistical analysis, operations analysis, data modeling, data quality assessment, exploratory data analysis, and quantitative problem-solving methods. • Experience creating reports, dashboards, charts, or visualizations using Tableau or similar business intelligence / visualization tools. • Ability to communicate technical findings, operational tradeoffs, and recommendations clearly to both technical and non-technical stakeholders. • Strong attention to detail, analytical judgment, and problem-solving ability.
• Experience or familiarity with big data or distributed data tools such as Spark, Hadoop, Cassandra, or similar technologies. • Experience working with engineering teams on data pipelines, analytical prototypes, model validation, automation workflows, robotics workflows, or production data workflows. • Experience analyzing product, operational, SaaS, automation, robotics, logistics, authorized penetration-testing, or security-assessment datasets.
Tech stack
PythonTableauSparkHadoop
About AutoRoboto
AutoRoboto is hiring for the data analysts role. NewJob aggregates active openings directly from AutoRoboto's applicant tracking system, so this listing is current.
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