Efaste Mushundusi

Data driven person, specializing in customer research in the MRO sector, third-party data matching, geospatial analysis, and data engineering. Experienced in transforming complex customer and business data into actionable insights through advanced analytics, data enrichment, and scalable data solutions.

Customer Information Researcher II – Customer Information Strategy Enablement at W.W. Grainger (2025-07 – Present)

• Conducted geospatial and address-matching analysis to quantify duplicate Customer Business Addresses, evaluate deduplication methodologies, and assess the feasibility and potential impact of building-level data consolidation.
• Collaborated with the Data Engineering and Product Management teams to develop business logic for identifying Grainger branches and improving organizational data visibility for stakeholders. As well as designed, tested, and documented multiple branch-identification methodologies, evaluating their effectiveness and providing recommendations on the optimal rule for implementation.
• Supported the Marketing Team in leveraging customer information data to estimate the population of locations and contacts associated with industries (NAICS Code) relevant to the LA28 event ecosystem. This resulting dataset was used to evaluate campaign strategies, quantify target audiences, and identify potential customer populations.
• Developed a Streamlit monitoring dashboard to track changes in Customer Information data, providing the team with greater visibility into data updates and supporting more informed data quality decisions.
• Supported the Order-to-Cash team in leveraging customer NAICS codes to determine when account restrictions could be lifted, enabling more accurate eligibility decisions for purchasing otherwise restricted products.
• Partnered with Data Governance to source third-party prospect contact data, evaluating data quality, completeness, and usability to address Marketing's contact data gaps and support campaign targeting.
• Analyzed 35 million potential customer prospects within Customer Information data to identify high-value, high-quality prospects for Marketing campaigns by combining square footage, revenue, and third-party data. As well as Developed prospect segmentation criteria to estimate the number of actionable prospects and support Marketing's campaign targeting strategy.
• I audited the Google Places API out-of-business indicator, documenting the accuracy of each business indicator and creating a visual chart for leadership. This analysis helped leadership understand the reliability of the Google API for Customer Information data validation.

Customer Information Researcher II – Customer Information Research & Design at W.W. Grainger (2025-05 – 2025-07)

• Collaborated with the Data Engineering and Product Management teams to support the implementation of Grainger's new Keepstock system, ensuring Customer Information data was verified and accurate for customer onboarding. And developed a Streamlit application to monitor weekly batch processing progress, improving operational visibility and providing leadership with an accessible dashboard for tracking implementation status.
• Performed customer contract analysis to identify accounts with missing contract assignments, enabling the team to address data gaps and ensure accurate alignment between customer accounts and contractual relationships.
• Supported the Customer Review Group by investigating and resolving our customer information data issue, including correcting university names and improving data visibility for stakeholders across approximately 3,900 customer accounts. And identified and documented university-related data issues in Customer Review Group presentations, communicating key findings and supporting data quality improvements.
• Integrated third-party data to develop a University System for higher education customer, standardizing customer names at scale and improving the accuracy of university data across more than 20,000 customer records. And reviewed, verified, and corrected university organization records to support the implementation of a new University System attribute for the University's Customer Review Group.
• Researched and implemented data fixes to improve the accuracy and representation of property management customer data, impacting approximately 7,000 customer accounts
• Applied the design thinking framework to identify the underlying data problem, understand business needs, and guide the development of an effective data quality solution.
• Created and maintained Confluence documentation to articulate project findings, document data fixes, and communicate the approach to teams and stakeholders.

Customer Information Researcher I – Customer Information Research & Design at W.W. Grainger (2022-09 – 2025-05)

• I actively participated in the team's efforts to profile and rectify any inaccuracies within Customer Information data. By addressing these errors, we were able to enhance our ability to accurately model and understand the dynamics of our customers, including significant events such as company changes and M&A activities.
• Analyzed and integrated third-party data with Customer Information data to identify missing NAICS codes and enrich customer records, improving data completeness and enabling more accurate analysis of company business activities.
• Applied Python and Seaborn to develop a heatmap comparing NAICS code classifications between Third-Party data and Customer information data, identifying areas of agreement and discrepancies to support data validation and refinement.
• Applied Jaro-Winkler similarity and other matching methodologies to improve the accuracy of matching Third-Party data sources with our customer data, helping bridge gaps and improve the completeness and reliability of the customer dataset.
• Applied confusion matrix analysis to evaluate the accuracy of data matching processes, assess matching reliability, and identify opportunities for methodological refinement and data quality improvement.
• Profiled third-party data sources to identify opportunities to enhance customer information and address data gaps. Integrated relevant third-party data into customer analysis to improve the understanding of customer characteristics and business needs. And developed the presentations to communicate data-driven insights and findings to teams and stakeholders.
• I collaborated closely with my teammates, aimed at matching third-party data with our Customer Information data. This joint effort proved invaluable in enhancing our comprehension of our customers' actual employee count. By leveraging this information, we were able to significantly improve the accuracy and effectiveness of our customer model. Our collaborative approach fostered a seamless integration of data sources, ultimately leading to more informed decision-making and optimized business processes.

Data Consultant – Data Engineering & Business Intelligence at One-Six Solutions, Inc (2022-02 – 2022-08)

• Supported the development of the client's internal data warehouse using Matillion ETL and Snowflake.
• Defined and documented detailed ETL specifications to support the design and development of the internal data warehouse.
• Collaborated with the Senior Manager to improve the client data warehouse for reporting and business intelligence use cases using Matillion ETL and Snowflake
• Documented client data mapping changes to maintain accurate source-to-target relationships within the data warehouse.
• Troubleshot client data issues and validated data accuracy to support reliable reporting.
• Developed foundational experience in integrating REST APIs with Power BI and performing source-to-target data mapping.
• Contributed to the development and maintenance of training resources to support internal knowledge sharing.

Bachelor of Science in Operation Management and Information System – Northern Illinois University College of Business (2019 – 2021)

Associate in Science in Business/Technology – Waubonsee Community College (2015 – 2017)