Data Analyst with a Software Engineering background, specializing in end-to-end data pipelines, statistical analysis, and business-facing dashboards. Proven track record of turning real-world data into decisions — across…
Data Analyst with a Software Engineering background, specializing in end-to-end data pipelines, statistical analysis, and business-facing dashboards. Proven track record of turning real-world data into decisions — across sensor streams, retail operations, e-commerce segmentation, and environmental modeling.
Built a full pipeline from data collection through cleaning, modeling, and automated PDF reporting, cutting manual overhead by 70%.
Trained a scikit-learn regression model for real-time CO2 emission prediction with 80%+ accuracy.
Delivered a Streamlit dashboard enabling stakeholders to identify a 15% emissions reduction pathway.
Built a full pipeline from data collection through cleaning, modeling, and automated PDF reporting — cutting manual overhead by 70%., Trained a scikit-learn regression model for real-time CO2 emission prediction (80%+ accuracy); delivered a Streamlit dashboard enabling stakeholders to identify a 15% emissions reduction pathway.
Built an end-to-end Python ETL pipeline ingesting live sensor data.
Validated 1,000+ data points in real time.
Reduced reporting effort by 60%.
Eliminated a key manual bottleneck.
Analyzed visual inspection data to track defect metrics at ±0.2 mm precision.
Identified root causes that improved safety scores by 80%.
Directly informed engineering corrective actions.
Designed operational dashboards used daily by the engineering team to monitor production KPIs across cross-functional stakeholders.
Built an end-to-end Python ETL pipeline ingesting live sensor data, validating 1,000+ data points in real time — reducing reporting effort by 60% and eliminating a key manual bottleneck., Analyzed visual inspection data to track defect metrics at ±0.2 mm precision; identified root causes that improved safety scores by 80%, directly informing engineering corrective actions., Designed operational dashboards used daily by the engineering team to monitor production KPIs across cross-functional stakeholders.
Wrote and optimized complex SQL queries to extract and analyze operational data across 500+ retail stores.
Surfaced patterns that informed executive-level reporting.
Translated stakeholder business requirements into data models and reporting structures.
Architected the data layer of an internal reporting tool.
Significantly reduced manual report preparation time.
Wrote and optimized complex SQL queries to extract and analyze operational data across 500+ retail stores, surfacing patterns that informed executive-level reporting., Translated stakeholder business requirements into data models and reporting structures; architected the data layer of an internal reporting tool, significantly reducing manual report preparation time.
Restructured the nonprofit’s digital data flow and information architecture.
Laid the groundwork for traffic and engagement analytics across performing arts programs.
Received a formal recommendation letter.
Restructured the nonprofit’s digital data flow and information architecture, laying the groundwork for traffic and engagement analytics across performing arts programs. (Formal recommendation letter received.)
•Analyzed 500,000+ e-commerce transactions; built an RFM scoring pipeline (Pandas) to segment 4,338 customers into 6 behavioral groups — identifying the 'At Risk' segment as the top recovery opportunity.•Delivered a Power BI dashboard visualizing segment distribution, monetary value, and recency to guide targeted marketing decisions.
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