Data Science A Team

PAUL AGBAJE

Minneapolis, MN • 763-***-**** • ********@***.*** • www.linkedin.com/in/paulagbaje

EXPERIENCE

CARLSON ANALYTICS LAB, Minnesota, USA July 2023 – Present Lead Data Science Consultant

Increasing crew pairing efficiency for a Top 10 US airline

• Built an interactive dashboard in Power BI to display key crew pairing efficiency metrics resulting in an $6M+ reduction in cost.

• Lead a team of 5 data scientists to build predictive models to optimize crew pairing scheduling saving 40+ hours/week of effort.

• Supported a team of MLOps engineers in deploying the machine learning model to production, using MLflow. Understanding participant likelihood of homeownership for top Non-Profit

• Employed Python for clustering and predictive modeling to identify key features impacting 180K+ participants' homeownership likelihood and potentially improving participants’ FICO scores to 590 and efficiency of resource allocations in the program by

$2M+. Validated factors contributing to home-ownership likelihood using a statistical regression model, built in R.

• Used Tableau to help clients understand analytics insights to boost resource allocation by 8% and identify key customer segments. STANDARD BANK GROUP, Lagos, Nigeria

Product Analyst, Software Delivery and Quality Assurance May 2021 – June 2023

• Led product delivery plans and developed product KPIs ensuring adherence to regulatory standards, to achieve 98% rollout success.

• Collaborated with internal and cross-border stakeholders, driving delivery of multiple strategic solutions including the card scheme, Afrigo, and internet banking revamp that have collectively generated financial returns of $30M+.

• Partnered with cross-functional teams to implement A/B testing, increasing click-through rates on loan products on IB channels.

• Used SQL to extract and analyze 3M+ financial transactional and customer data from Oracle and Microsoft SQL Server databases, generating 8+ business intelligence reports for strategic decision-making, and providing data for statistical inference & UAT.

• Helped deploy an end-to-end customer churn model using Python, and improved customer retention by 3%.

• Worked in a team of 6 to deploy revamped web applications using usability testing, and prehistoric usage metrics (e.g. bounce rates). The new web applications had an average increase in traffic by 7%.

• Monitored product and API Performance during the alpha and beta phases to provide usage data and inform resource allocation. TELNET NIGERIA LIMITED, Lagos, Nigeria

Technology Analyst, Special Projects January 2020 – April 2021

• Constructed a real-time reporting tool with PowerBI for the Central Bank to standardize trade metrics across countries and banks.

• Improved targeting effectiveness by 32% by segmenting customers across 20+ territories in the region using unsupervised learning.

• Built a traditional time-series forecasting model to achieve a 14% improvement in sales forecast accuracy. EDUCATION

UNIVERSITY OF MINNESOTA, Carlson School of Management, Minneapolis, MN Candidate for Master of Science in Business Analytics – Data Science and Analytics Focus (GPA – 3.7) May 2024 UNIVERSITY OF SURREY, Surrey, United Kingdom

Bachelor of Engineering – Biomedical Engineering (GPA – 3.8) July 2019 ANALYTICS AND ARTIFICIAL INTELLIGENCE (LLM) PROJECTS

• Generative AI: “Open AI-driven review intelligence” – Created a program that uses customer sentiment data using Spark for batch processing and LLMs with prompt engineering, to understand customer sentiment trends outperforming current NLP methods link.

• Generative AI: “Categorization of Medical Transcription for Health Care Notes” – Worked as a research assistant to develop chatbots that help categorize medical transcriptions into doctor’s notes optimized for querying using Langchain and GPT-3 link.

• Time Series Forecast: “Walmart Weekly Sales Forecast” – Trained a LightGBM and deep learning model to accurately forecast Walmart sales for 4 weeks in the future with a prediction error of 6% less than other external regressors link.

• Data analytics: “Bioscience” – Ran experiments using red blood cells (RBCs) in different solutions and created a model to predict the Zeta potential in RBCs with MATLAB which has implications in predicting the likelihood of a heart attack. Publication: link.

• Causal Inference: “Freelance” – Measured user engagement and retention on a client's website using a propensity-matching logistic regression model and successfully increased mobile coupon redemption by 11.5%. SKILLS, ACTIVITIES AND CERTIFICATIONS

• Tools: Python, SQL, R, Spark, Hadoop, Tableau, GitHub, Excel, MongoDB, JavaScript, Alteryx, Linux, Adobe Analytics, JIRA.

• Techniques: Predictive Modeling, NLP, Exploratory Analysis, Statistical Analysis, Time Series Forecasting, A/B Testing, ETL, Casual Inference, Data Visualization, MLOps, Anomaly Detection, Machine Learning Algorithms, Propensity Score Matching.

• Certifications and Training: AWS (Developer Associate candidate), Azure (AZ – 900), Salesforce Trailhead, Tableau (LinkedIn), Mckinsey forward program.

• Interests: Pro-bono technical consultant (Ortarkie and Bunny Besties), Podcasting (Founder and Host of “What it takes”).

Contact this candidate