Data Analyst
October 2
Description
• Documentation, Reporting, Root Cause analysis of Prediction issues. • Analyze ingested and system-generated data for anomalies and gaps. • Refer to various data sources to plug those gaps. • Create data stories and come up with possible solutions in terms of QA process flow change and/or automation. Own the subsequent plan and execution. • Automation of Performance/Accuracy review processes, report generation, data visualization using Python, SQL. • Support engineering and data science teams in system-level data fixes. Understand how the engine makes predictions, explore possible improvements in the process by fixing/introducing new data/features. • Support the customer operations, marketing team in getting insights from the data, such as performance, accuracy metrics, impact of real-time events, etc. as required. • Maintain, own internal and customer dashboards based on the trial/account requirements (e.g. prediction accuracy, timeliness, coverage, explainability).
Requirements
• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field. • Prior experience in data analysis or data analyst roles, preferably in a startup environment. • Exceptionally skilled in Python and SQL, with a demonstrated ability to consistently produce reusable and highly scalable code. • An eye for detail: Looking for anomalies in the system. • Familiarity with Linux, GitHub, product development. • Proven experience with data visualization. • Empathy and Urgency: to feel the customer pain and react promptly on a day-to-day basis • A Problem solver & go-getter: either programmatically or manually meeting customer expectations and delivering on time. • Fluent with written and verbal in English. • Strong ownership mindset, efficiency, and data-driven approach. • Good to have: basic understanding of machine learning algorithms.
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