Be a part of the CEO's vision for the next generation of performance management. As a Data Analyst on the AutoPH team, you will be responsible for collecting, analyzing, and interpreting data to help optimize AutoPH processes, improve system accuracy, and support decision-making. This role involves working with large datasets from various systems and tools, identifying trends, generating reports, and providing actionable insights to support operational, project, and business objectives.
Data Modeling & Algorithm Optimization: Evaluate AutoPH logic to improve measurement precision, reduce bias, and build mathematically sound performance metrics.
Data Collection & Management: Gather and organize data from various sources, including internal systems, and project databases, ensuring data integrity and accuracy.
Data Analysis & Reporting: Analyze large datasets to identify trends, patterns, and insights that can inform talent decisions, improve system performance, and optimize processes.
Quality Control: Ensure the accuracy, consistency, and reliability of data through validation, cleaning, and preprocessing techniques.
Pipeline Automation: Develop and implement tools or scripts to automate data collection, analysis, and reporting tasks, improving efficiency and reducing manual effort.




Cross-Functional Collaboration & Technical Writing: Convert high-dimensional data and complex analytics into clear, low-friction narratives for C-suite decision-makers.
Root-Cause & Trend Analysis: Investigate system anomalies, analyze performance trends, and track core KPIs to continuously improve system reliability.

Required Skills & Experience
Experience: 3+ years in a high-growth environment (Product, Fintech, or Strategy & Ops); Tier 1-2 MBA/B.Tech required.
Advanced SQL & Modeling: Solid hands-on proficiency with SQL and Google Sheets/Excel for complex modeling; familiarity with BigQuery is a plus.
Hands-on experience building interactive dashboards in Power BI, Tableau or Data Studio.
Working knowledge of Python or R for data cleaning, preprocessing, and basic automation.
Analytical Skills: Strong foundational statistics, data validation techniques, and root-cause analysis skills.
Proven ability to explain technical insights to non-technical managers and executive stakeholders clearly.

Takes ownership of complex data pipelines while maintaining high standards for accuracy and logic.
Agile & Driven: Thrives in fast-paced setups, managing tight deadlines and cross-functional dependencies with resilience.

📌 Specialist Data Analyst / Data Analyst (Hyderabad)
🏢 HighRadius
📍 Hyderabad