• Collaborate closely with senior management, including C-Level Executives and VPs/Directors, to ideate, formulate projects, and drive progress towards strategic goals.• Designed and implemented a Lead Scoring model for 1.3M non-OFP leads using machine learning (gradient boosting) in Python that has been utilized by 200+ sales reps. Since implementation of the model, yearly revenue from non-OFP leads has increased by $4,000,000/year.• Designed and implemented an NLP application that matches prospective customers to our product offerings based on user input. Employed Generative AI and Retrieval-Augmented Generation (RAG) techniques to analyze target audiences and deliver tailored product recommendations.• Developed and deployed a Recommendation System in Python that leverages historical sales performance data to connect Sales Reps with prospective clients from inbound sales inquiries.• Developed sales forecasts and identified trends using time-series techniques such as Generalized Additive Models (GAMs).• Lead Causal Inference/Quasi-Experimental efforts to measure the impacts of business initiatives on strategic KPIs.• Identified ineffective or damaging company policies that were losing the company an estimated $700,000 year using statistical techniques such as OLS Regression. • Contributed to a 35% reduction in delay rates for our Brief product line campaigns by identifying trends/root causes using SQL and R.

• Designed and maintained 40+ monthly CPU forecasts for servers using a combination of time-series methodologies & qualitative input from SMEs using R and Shiny. • Estimated and evaluated the effectiveness of several marketing campaigns using non-parametric hypothesis testing methodologies in R.• Designed and generated several time-series forecasts for multiple departments utilizing techniques such as XGBoost, GBMs, and Regression in R and H20.

• Collaborated with business leaders across multiple departments to design and implement KPIs across 200+ reports and dashboards through SQL/Tableau/SSRS.• Collaborated with several cross-departmental executives to design and implement Betenbough's first Employee Satisfaction survey, which had a response rate of 80%+, and lead to several high-impact changes to business operations across multiple departments. • Contributed to increased Market Intelligence through advanced pricing analytics. Projects include estimating price elasticities and market inflation via logistic regression in R.• Identified predictors of team health via logistic regression in R, resulting in changes to business practices.