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Remote, mid-level generalist data role attracts high applicant density across locations.
Skills transferable across industries, but logistics-focused predictive data-quality experience increases domain specificity.
Mandatory 3+ years plus strong Python/SQL and data-quality ownership enforces moderately strict shortlisting.
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Own end-to-end data quality and anomaly detection for prediction engine feeding global supply chain visibility platform.
Lead root-cause analysis of prediction issues, propose fixes in QA process or automation, and execute improvements.
Automate data review, reporting, and maintain internal/customer dashboards reflecting prediction accuracy and performance metrics.
Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or related field.
3+ years experience as Data Analyst or Business Analyst, preferably in product-based startup environment.
Strong skills in Python and SQL with focus on reusable, scalable code.
Work Experience Required: At least 3 years in relevant analyst role.
Data analyst with a strong ownership mindset who proactively tracks down data anomalies and fixes root causes rather than applying patch solutions.
Experienced in building reliable, reusable data pipelines and dashboards with high data quality standards.
Comfortable collaborating across Data Science, Engineering, Product, and Commercial teams in a remote, diverse environment.