Data Analyst (Temporary Maternity Leave Replacement)

About The Position

About the Position

At Harmonya, we’re proud to be at the forefront of the AI revolution. As a Data Analyst on the DataOps team, you’ll 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 who’s 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.

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 teams—including Product Managers, Data Scientists, Engineers, and Labeling Specialists—to understand user needs and ensure the delivery of robust, scalable ML solutions with high-quality data throughout the pipeline.

Requirements:

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.

Advantages

• Experience working with or alongside Data Scientists.
• Familiarity with data science workflows and processes.
• Practical experience with Python.
• Knowledge of statistics and statistical thinking.
• Exposure to projects involving machine learning or predictive modeling.