Efe U.

About Efe U.

Data Scientist with 5+ years of proven expertise transforming complex datasets into strategic business outcomes across automotive and energy industries. I specialize in machine learning, statistical modeling, and large-scale data engineering, delivering measurable impact through advanced analytics and cloud-based solutions.CORE EXPERTISE & IMPACT: At Ford Motor Company, I led high-stakes analytics initiatives analyzing 50M–150M customer records. I managed a $36M parts cost gap investigation using Python and BigQuery, reducing the cost gap by 45% and increasing service center Net Promoter Score (NPS). I built ML models on 100M+ customer records, establishing NPS KPIs that strengthened customer trust and enabled accurate satisfaction measurement.TECHNICAL CAPABILITIES: I architect end-to-end data solutions across GCP, Snowflake, BigQuery, Databricks, Hadoop, and Spark. My machine learning toolkit spans predictive analytics, neural networks, decision trees, clustering, time series forecasting, and NLP. I build production-grade ETL pipelines processing 100M+ records, engineering customer experience features for downstream ML applications.DATA VISUALIZATION & BUSINESS INTELLIGENCE:I translate complex analyses into executive-ready insights using Tableau, Power BI, and Looker. My data storytelling bridges technical depth with business accessibility, enabling stakeholders to make confident data-driven decisions. I\'ve standardized analytics workflows and implemented robust data governance with automated reporting dashboards.CLOUD MIGRATION & INFRASTRUCTURE:I\'ve planned and executed cloud migration strategies, transferring 10TB of data to GCP, reducing infrastructure costs. Experience with SAP BusinessObjects, Teradata, SAS, IBM SPSS Modeler, and modern cloud data warehouses.STATISTICAL MODELING & RESEARCH:With a Master\'s in Applied Statistics, I apply rigorous statistical methodologies including regression analysis, hypothesis testing, experimental design, and fraud analytics. Improved forecasting accuracy by 25% and process efficiency by 15% through statistical optimization.LEADERSHIP & COLLABORATION: I elevate data literacy across organizations by designing speaker series (averaging 100 attendees) and mentoring cross-functional teams. I standardize customer insight analytics across teams, improving data accessibility and collaboration.INDUSTRIES & APPLICATIONS: Automotive, energy, customer analytics, operational analytics, fraud detection, predictive maintenance, customer experience optimization.

Experience

1. Data Scientist

   Ford Motor Company

   Jun 2021 — Present · Dearborn, MI, US

   Leading high-impact analytics initiatives for Ford\'s Smart Mobility division, specializing in customer analytics and enterprise data management. Analyzing 50M–150M customer records using Python, BigQuery, and machine learning to drive measurable business outcomes and strategic decision-making.Key Achievements & Impact:• $36M Cost Reduction Initiative: Spearheaded comprehensive parts cost gap investigation using Python and BigQuery, analyzing 50M+ customer records across multiple data sources. Identified root cause drivers and developed actionable recommendations that reduced cost gap by 45% and improved service center Net Promoter Score. Delivered executive presentations translating complex statistical findings into strategic business insights.• Machine Learning & Customer Experience: Built production machine learning models including decision trees and neural networks on 100M+ customer records, establishing Net Promoter Score KPIs that enabled accurate customer satisfaction measurement. Models strengthened customer trust metrics and provided predictive capabilities for proactive service improvements.• Enterprise Data Standardization: Led standardization of customer insight analytics across Smart Mobility\'s Predictive Repair Intelligence team by implementing enterprise data management practices. Architected data governance frameworks using SQL, Hadoop, and Google Cloud Platform that improved data accessibility, cross-team collaboration, and accelerated data-driven decision velocity.• End-to-End Analytics Infrastructure: Developed comprehensive data wrangling, experimentation, and visualization workflows using Python, BigQuery, Looker Studio, and Alteryx. Created automated dashboards delivering actionable insights and executive-ready reporting for C-suite stakeholders. Enabled self-service analytics capabilities across business units.

Education

• California Baptist University

  Bachelor's degree, Mathematics

• Azusa Pacific University

  Master of Science - MS, Applied Statistics and Analytics