Lawrence Karongo
Greater-Seattle, WA
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614-653-4567
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lawrencekarongo@gmail.com
BI & Analytics Platforms: QuickSight, Adobe Analytics (familiar), Power BI, Tableau
Cloud & Data: AWS Glue, Redshift, S3, Athena, SageMaker
Languages: Python, SQL, PySpark, Spark SQL
Analytics: A/B Testing, Funnel Analysis, Seller & Customer Analytics, Segmentation, Simulation
Education
Master of Public Policy in Advanced Policy Analysis
University of Minnesota Twin Cities
May 2017
Bachelor of Science in Applied Economics
University of Minnesota Twin Cities
May 2015
Professional Experience
Amazon
Business Intelligence Engineer II – Fulfillment Technology AI
April 2024 – Present
- Rapidly onboarded to new analytics platforms and tooling to meet evolving business requirements, demonstrating ability to transfer BI expertise across diverse technical environments.
- Developed executive-facing QuickSight dashboards with self-service capabilities, enabling stakeholders to explore operational, business, and model performance data independently, reducing ad-hoc reporting requests by enabling data-driven decision-making.
- Designed user-specific data visualizations and dashboard layouts through iterative stakeholder feedback, ensuring insights were accessible and actionable for non-technical audiences.
- Built ROI and forecasting simulations to model entitlement gains and long-term business impact, guiding strategic prioritization and resource allocation across fulfillment centers.
- Defined and owned core KPI frameworks for SKU image coverage, applying experimental analysis and causal reasoning to quantify incremental impact and justify leadership investment.
- Designed and implemented AWS Glue and Spark Framework ETL pipelines, unifying multiple S3 and data lake sources to support metric production, experimentation analysis, and dashboard automation.
- Productionalized Spark SQL pipelines to deliver timely ETL outputs aligned with program requirements, ensuring data reliability for downstream analytics and leadership reporting.
- Delivered four analytical products across three domains in six months, demonstrating strong prioritization, cross-functional communication, and end-to-end ownership.
Business Analyst II – Selling Partner Services
June 2022 – April 2024
- Conducted customer (seller) journey and funnel analysis using behavioral data to identify friction points and conversion opportunities, informing product and engagement strategy.
- Developed a large-scale NLP sentiment dataset integrating open-text models to surface behavioral signals, enabling targeted interventions based on member feedback patterns.
- Built automated metric deviation alerting pipelines (Glue + Python), improving operational response times and enabling proactive issue identification.
- Conducted ANOVA and regression-based analyses to evaluate predictive power of trailing metrics on seller satisfaction, strengthening forecasting accuracy and engagement modeling.
- Designed and maintained ETL pipelines supporting experimentation, feature engineering, and automated reporting across multiple business lines.
Previous Experience
Institutional Data Analyst
Charles R. Drew University of Medicine and Sciences
Aug 2020 – June 2022
Data Scientist
East Bay Community Law Center
Aug 2018 – July 2020
Star of the North Fellow
Minnesota Department of Transportation
June 2017 – July 2018
Research Assistant
University of Minnesota Twin Cities
Aug 2014 – May 2017