were proud to be at the forefront of the AI revolution. As a Data Analyst on the DataOps team, youll play a key role in ensuring the integrity and reliability of our data systems. Your primary focus will be on data quality assurance auditing datasets, identifying anomalies, validating transformations, and ensuring consistency across our machine learning pipelines. This role is ideal for someone whos passionate about data, detail-oriented, and eager to support high-impact AI solutions. We're looking for a data analyst with strong analytical skills and a commitment to maintaining data quality at scale.
Conduct data audits and validation checks to ensure accuracy, completeness, and consistency across diverse data sources.
Conduct data audits and validation checks to ensure accuracy, completeness, and consistency across diverse data sources.
Responsibilities
Perform exploratory data analysis to identify anomalies, edge cases, and inconsistencies that could affect model performance.
Automate and monitor data quality by building tools, dashboards, or queries, and by investigating root causes of data issues, proposing improvements, and tracking their resolution.
Evaluate external data sources for usability, schema compliance, and alignment with business goals.
Collaborate across teamsincluding Product Managers, Data Scientists, Engineers, and Labeling Specialiststo understand user needs and ensure the delivery of robust, scalable ML solutions with high-quality data throughout the pipeline.
Requirements:
At least 2 years of experience in data, analytics, or QA roles.
Fluency in written and spoken English at a professional level.
Strong attention to detail and the ability to work independently while maintaining accuracy and efficiency.
Excellent verbal and written communication skills.
Critical thinking and strong problem-solving abilities.
Basic knowledge of SQL and familiarity with databases or query languages (SQL preferred).
Proven experience in improving or overhauling analytical processes or tools.
At least 2 years of experience in data, analytics, or QA roles.
Fluency in written and spoken English at a professional level.
Strong attention to detail and the ability to work independently while maintaining accuracy and efficiency.
Excellent verbal and written communication skills.
Critical thinking and strong problem-solving abilities.
Basic knowledge of SQL and familiarity with databases or query languages (SQL preferred).
Proven experience in improving or overhauling analytical processes or tools.
This position is open to all candidates.
