• 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, exploitability)

• 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