John Hinkle Email & Phone Number

United States

Cleveland , Ohio, Us

• Served as lead developer on a recommendation system model that utilized gradient boosted and random forest tree algorithms to provide relationship managers optimized product leads, estimated to drive $150M in incremental revenue over the next 3 years• Developed a challenger approach to the recommender model with an unsupervised learning method using hierarchical clustering• Led weekly meetings with business leaders and modelers, facilitating cross-functional communication during model development• Co-authored a paper addressing the Fed’s concerns regarding the bucketing strategy of credit risk ratings by creating Python scripts to produce charts and tables analyzing risk rating stability and migration paired with narrative describing the impacts• Transitioned and restructured the segmentation and variable creation data processing pipeline code from SAS to Python for the entire commercial book, analyzing the impact of subsegment composition and portfolio migration for future loss forecasts• Mentored a rotational analyst in the development of a scorecard model and its documentation for 6 portfolios over 6 months

Cleveland , Ohio, Us

• Contributed to the model development of the Commercial & Industrial Credit Modeling Team’s Business Banking CCAR model • Updated the forecasting and back testing Python code of the Business Banking CCAR model to support the CECL assumptions about loans that CCAR regulations do not include in order to perform the testing on the team’s CECL model • Authored two Python scripts for the Market Risk Team, one to obtain foreign exchange forward rates and interest rate curves from SQL and output an Excel summary table of risk factors based on currency and tenor, and another to analyze treasury securities’ impact on the pricing differences of KeyBank’s fixed income securities compared to external broker pricing

Arlington, Va, Us

• Performing market, customer, and product research to support contract acquisition and service reports for company use• Authoring the company’s official newsletter, with direct communication to the CEO and Head of Human Resources, to publish an informative monthly report on the market within the defense industry as well as serve as a liaison for information and directives from corporate to the entire company• Developed and implemented Applicant to Employee Tracking System to record and analyze onboarding and recruitment metrics

Newark, New Jersey, Us

• Built a natural language processing model in Python to produce the top key unigrams in service call notes that would predict customer complaints using historical complaints data and 3 years of past service call notes to flag potential complaint clients• Created a sentiment analysis model in Python with input functions to generate bigrams and trigrams that predict complaints• Designed dashboards in Power BI to provide a visual breakdown of demographic data of customers who have replaced insurance in order to give insight on the cause-and-effect relationship between customer complaints and insurance replacement• Worked on the Model Risk Review team to assess the implementation and methodology of Python models from a newly acquired company to ensure proper functionality before integrating them into Prudential’s line of business

Charlotte, North Carolina, Us

Charlotte, North Carolina, Us

• Managing chapter finances through the development of a $100,000+ budget, collecting dues, allocating funds, communicating with committee chairmen, and tracking chapter and committee expenditures • Collecting $151,600 in chapter dues from 160 men, distributing $115,000 to 11 committees, and bestowing $10,000 of philanthropic gifts to The Ability Experience

Charlotte, North Carolina, Us

• Analyzed the outcome of deals within the Pricing Deal Desk Tracker to test current pricing hypotheses and investigate whether benchmarking current opportunities against passed deals is statistically significant in affecting the team’s win-loss ratio• Assembled data to assist in the development of pricing models for 5-10 live deals on a weekly basis to present in Level 3 pricing approval meetings as a predictive evaluation of the specific opportunity with the goal of a 1% gross margin increase• Utilized Tableau to create a dashboard displaying 4 dynamic price per point distributions for 2000+ deals based on product line that can be altered to fit a certain criterion of opportunities to provide a statistical breakdown of data and insight on price per point• Automated in Excel 8 discount scenarios down to the unit level pricing for specific opportunities allowing for greater analysis to be done on how a change in discount for a certain opportunity impacts win rates for that deal

Rolling Meadows, Il, Us

• Provided consultative services to companies creating client-specific go-to-market strategies evaluating the results of benchmarking the client's risk program to competitors and assessing the client's unique program structure• Modeled cyber insurance coverage for 5 municipalities and 8 school zones in the state of Florida researching specific coverage against premium costs to ultimately determine optimal risk management programs for each based on 6 cost drivers• Presented weekly industry topics to the office of 40 employees and composed reports within field to Orlando branch

Orlando, Florida, Us

• Surveyed the waters of one of America’s largest waterparks, watched over and protected the 15,000 people that visit on a daily basis exemplifying mastery in CPR and use of an Automated External Defibrillator in various situations • Constructed schedules and served as the main first responder to any potential hazards and problems and in constant contact with the Aquatics Team Supervisors for the entire resort

Plymouth Meeting, Pennsylvania, Us

• Promoted to the Valet Guest Service Associate, at a hotel visited by 8.3 million people a year, supervised the hotel guest arrival ramp and all car services the hotel offers (i.e. self-parking, daily parking, and valet parking) • Managed and tracked data input on all vehicle transactions to ensure accurate processing of the 400+ check-ins a day • Handled both the floor work of running for cars and kept ramp access clear as well as serving as the Royal Pacific Car Services Cashier and Resource Guide to more than 2,500 guests

Master Of Science - Ms, Information Systems And Operations Management

Bachelor Of Science In Business Administration, Finance

Minor, Actuarial Science