Dan Basco Email & Phone Number

Cleveland, Oh, Us

• Build logistic and linear regression models in Python designed to forecast financial performance of portfolio segments. Score models quarterly and provide results to the Finance team.• Lead analyst for our Model Risk Management project. Validate and monitor predictive models within our bank. Ensure tasks are completed on time and accurately. Assess new models added to our inventory.• Perform ad hoc data analyses using financial data and present results to internal business partners. Areas of analysis include credit fraud, credit limit increases/decreases, card reissues, credit scoring, and credit risk.• Assess which variables from new data tables need to be loaded for ongoing data analyses. Check accuracy of data tables against other data sources.• Work with third parties for the implementation of new vendor models.• Created time series forecast to predict future sales on new credit card. Presented results to CFNA President.• Designed Adaptive Control System (ACS) strategies for credit limit increases and decreases.• Served on CFNA Leadership Council. Worked with Human Resources to implement action plans based on feedback from employee surveys.• Provided monthly and quarterly updates on our key portfolio metrics related to origination, account management, and delinquency.• Evaluated the profitability of customer segments based on their credit score.• Set up test-and-learn experimental designs for e-mail and direct mail marketing campaigns. Analyzed the performance and presented the results to the marketing team.• Completed Bridgestone’s Leadership Development Program (Ignition).• Completed Python DataCamp Training and Introductory Tableau training.Skills: Python · Predictive Modeling · Data Mining · Statistics · Data Analysis · Problem Solving · Teamwork · SAS Programming · Statistical Consulting · Project Management · Adaptive Control

Cleveland/Akron, Ohio Area

• Lead analyst for rollout of countrywide model for several states. Made modifications to countrywide model based on legal restrictions. Presented model and state variations to internal business partners. Taught this process to junior teammates.• Modified R code to calculate expected change in insurance rates for different states after a model upgrade. • Analyzed unstructured third-party data (numeric data and text fields). Presented findings to management and made recommendations based on results.• Rewrote complex code in SAS to reduce complexity, increase accuracy, and reduce runtime.• Completed Data Science for Analysts in R training (Decision Trees, Random Forests, GBM)

Columbus, Ohio Area

• Led internal coding efficiency project; created a checklist of requirements (with example SAS code) needed to transform model development code into model scoring code for monthly execution.• Rebuilt expected spend and attrition models for a top tier client. Reduced the code runtime by 18 hours and the monthly data storage by 64 GB. • Lead analytic contact for top-tier clients. Collaborated with non-technical partners to design marketing strategy utilizing predictive modeling. • Built statistical models in SAS using logistic regression, linear regression, survival analysis, and cluster analysis.• Designed tradeoff surveys to assess cardholder preferences of benefit packages. Analyzed results using Sawtooth and SAS; presented recommendations to internal and external partners.• Used text mining in R to compile word frequencies and word clouds of survey responses.• Completed comprehensive portfolio assessment of credit card programs.

Columbus, Ohio Area

• Used SAS/SQL to extract credit, transactional, and demographic data from data warehouse tables. Addressed missing values and outliers.• Built model in R using linear regression and time series to forecast calls per week for call center. • Built and utilized linear and logistic regression models in SAS to identify suitable segments for marketing offers. Models helped increase cardholder retention rate, cardholder sales, and store traffic. • Analyzed effectiveness of mailing campaigns and credit card reissues using financial metrics.

• Taught several computer lab sections of Statistics for Everyday Life course. Assisted students with Minitab assignments.• Graded labs and recorded lab scores for several computer lab sections of Statistics for Everyday Life course. • Tutored students enrolled in Statistics for Everyday Life or Basic Statistics courses.

• Co-authored two articles describing technical details of advanced baseball statistics.• Proofread articles for summer issue of Baseball Research Journal.

Master Of Science, Statistics

Graduate courses: Statistical Data Management, Regression, Experimental Design, Database Management, Data Mining, Survival Analysis.

Bachelor Of Science, Electrical Engineering

Activities and Societies: Rocket Marching Band, Varsity Band, Symphonic BandGPA: 3.3 Minor: Mathematics

Education record