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.
Responsibilities- 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.
Qualifications- 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.
Preferred Qualifications- 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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
