Manage machine learning and analytics projects through entire project lifecycle – gathering requirements, building models / solutions, and delivering to stakeholders

Worked with FS & TMT group (financial services, technology, media, telecom) on initiatives across multiple clients and internal teams• Applied machine learning to develop customer “DNA strands” to be used for personalization efforts of top U.S. telecom company› Leveraged NLP and unsupervised learning to create 15+ strands, score customers on each based on web browsing behavior› Used machine learning to determine most predictive strands for different purchasing behavior• Assessed current state of data/analytics at large US independent broker-dealer; designed target state and roadmap to get there• Led creation of roadmap to map analytical solutions for all objectives of marketing team within top global technology company• Automated PDF invoice generation with universal VBA solution scalable to all clients, saving 5-10 man-hours per month per project

Served as data analytics consultant to base marketing teams of multiple brands within a top-3 U.S. telecommunications company:• Worked closely with analytics team to build customer propensity models and leverage models to deliver actionable insights• Used supervised and unsupervised learning to segment customer base and implement personalization for marketing campaigns› Generated 3x growth in monthly marketing touches and 1.5x growth in monthly revenue uplift over 6-month period• Set up A/B tests to understand performance of campaigns and scale up positively performing campaigns across customer base• Designed reporting dashboards in Excel that allow clients to monitor KPIs and streamline decision-making• Performed financial modeling to project future revenue impact of different initiatives • Communicated directly with key client stakeholders daily

Took on the roles of lead coder and project manager within group of MSBA classmates:• Cleaned and deduped insurance claim data from three hospital systems • Derived relevant features to build training data set • Built classification model using Python to predict if health insurance claims would be denied -- 91%+ accuracy for returning patients and 86%+ accuracy for new patients • Extracted most predictive features and identified strategic focus areas to minimize future denials • Presented model and insights to leadership team at VisiQuate

• Researched investment opportunities within the energy sector (oil & gas, renewables, etc.) • Built type curve models to project future performance of producing oil and gas wells• Educated colleagues on some more technical aspects of petroleum engineering and the oil & gas industry

• Analyzed data on reservoir acid stimulation and recommended action to increase performance and reduce spending on future job• Diagnosed performance of pumping units and recommended changes to optimize system and increase efficiency and production• Designed procedures for well work overs on failed ESPs (Electric Submersible Pumps)• Observed a variety of field procedures (acid jobs, perforation runs, ESP tear downs, etc.)• Presented conclusions and recommendations to Hess's engineering management team in Houston, TX.

• Collected and analyzed data to evaluate drill bit effectiveness and recommend bits for future use • Pulled data from DrillingInfo and New Mexico OCD to analyze production trends in Wolfcamp development (Midland Basin)• Observed variety of field procedures (horizontal drilling, plug & perf hydraulic fracturing jobs, gas lift installations, etc.)• Attended gas lift training at Lufkin facility in Midland, TX• Toured Baker Hughes oil tool facility in Midland, TX• Presented conclusions and recommendations to management team in Plano, TX

• Designed well bore diagrams for hundreds of wells in the Ozona Field of the Permian Basin• Observed practices of a team of production engineers.