- Product Owner for the Canadian Consumer Spend Momentum Index (SMI) which tracks and estimates consumer sentiment and spending patterns, andisa International Travel Index (VisIT) which we used to model near real-time domestic and international travel and spending patterns. - Expanded the SMI product line to include demographic breakdowns, issuer and industry specific indices, and aggregated issuer and industry tiers which provided a more granular picture for small communities, businesses and industry segments. The expanded product line more than doubled the original revenue stream. - Rewrote the existing VisIT program using an XGBoost model in pySpark to launch the project at scale, this enabled us to augment the data and models for better performance, and facilitated extensions beyond the original scope, including spend forecasts as well as demographic breakdowns. These new features increased revenue stream by more than 10X. - Led an effort to migrate all production processes from hive/Excel hybrid models to pySpark and then automated these processes via Airflow (DAG scheduler), which cut down on processing time and reduced load on team members. - Served as a “Tech Champion”, which is a conglomerate tech specialists that help the broader team diagnose any workflow, modeling, or data issues. Within this role, I led the effort to leverage the use of LLMs to aid in application templating, and worked with legal to build an in-house version for knowledge sharing of data products. - Served on the Social Committee, helping to plan activities that help with employee morale, and a lighter work atmosphere. I organized wine & paint events, happy hours, tea tastings, and led a demonstration of cocktail mixology.

Charter Communications | May 2017 - Jul 2020

Principal Experimentation Architect

- Lead the design effort to build the analytics engine behind experimentation and hypothesis (A/B) testing across all consumer facing products at Charter, including the video streaming app, buy-flow, and Customer Support apps. Scoped and prototyped in R and Hive and subsequently implemented in spark and automated using Azkaban (DAG scheduler), pulling event-level data from from a peta-scale data lake. Analysis included p-values, confidence intervals, power estimations, and the option of paired testing (i.e. longitudinal analysis). I built dashboards to model KPI metrics to better understand sensitivity, as well as assist with experiment design to better estimate duration and sample size requirements. - Served in a tech leadership role for experimentation and A/B testing company-wide, directing research to develop processes, KPIs, and experimentation road maps across the product portfolio. This included designing experiments, and follow-on experiments iterating on past outcomes, helping stakeholders to understand results, and teaching stakeholders to interpret successes and failures of experimental features. - Managed three other data scientists on the experimentation team. I worked with my team to design project roadmaps to evaluate experiment objectives, assisted with KPI development, and then worked with them to organize and present results to stakeholders. My team ranked #1 in stakeholder satisfaction across all of Product Insights for 3 of 4 periods. - Authored and delivered statistical and experimentation training to 100+ stakeholders up to C-Level across the company, ensuring that experiments aligned with business KPIs and were executed faithfully and with statistical rigor. - Participated in the internship program managing four interns during my tenure, creating an SOW and project milestones, and ensuring their work aligned with their career goals. - Organized happy hours for the broader team and facilitated a series of brown bag lectures focusing on learning from mistakes which featured VP’s from around the company speaking about teachable moments from career mistakes.

Level 3 Communications | Mar 2013 - May 2017

Sr. Quantitative Analyst

- Performed price optimizations for Metro and Intercity Wavelength products, High Speed Internet (HSIP), VPN, and out-of-term contract re-rate pricing models. I used various GLM regression and ML techniques to generate elasticity models to optimize monetization of the product. I provided recommendations on strategy and roll-out, presented to product owners and C-Suite executives. - Using a ensemble ML model (Random Forest, Logit, GAM), I launched a revenue optimization framework for the VPN product. US managers estimated excess profit growth of roughly $11MM above initial targets as a result of this model. - Built logistic regression bid optimization model for HSIP in R and python and deployed to the cloud using Flask. After a successful US launch, the model was deployed to EMEA where the HSIP product reversed years of revenue decline and saw revenue growth for the first time in four years, and maintained that growth for the rest of my tenure. - Lead price rationalization efforts during acquisition of Time-Warner Telecom to align pricing strategies for VPN and HSIP products. Target completion was four months, and I delivered a month early. My team received Quarterly Excellence Award from the CMO for the successful launch. - Built reporting/governance web dashboards using Shiny to auto-generate various analytics for performance evaluation and trajectory tracking in order to detect anomalous behavior in our products. This included an auto-recalibrating forecasting feature to predict price trends across several products in order to validate revenue and EBITDA. - Competed in annual intracompany Hackathon challenges, placing 1st in all instances, then was asked to join the model evaluation board and judges panel.

Bentek Energy | Jul 2013 - Nov 2013

Energy Analyst

- Automated the recalibration process using R for various natural gas demand forecasting models, tracking changes in coefficients over time to look for structural breaks in each model, reducing the recalibration time from one week to four hours. - Built a coal-power generation forecasting tool to achieve better predictive power in coal-gas fuel switching in order to increase transparency for the end users. - Developed a coal production forecasting model which was included in Bentek’s daily U.S. Power Burn Report distributed by Platts.

National Renewable Energy Laboratory | May 2012 - Nov 2012

Economist

- Worked with the Colorado Center for Renewable Energy and Economic Development to look at outcomes of the CleanTech market sector - Designed and built a model to track job growth as it pertains to the Cleantech market sector in Colorado using data from the Colorado Department of Labor and Employment. - Developed a method for reliable tracking of Records of Invention (ROI’s) within the scientific community at NREL, as well as for tracking ROI outcomes and efficiency within each research center. - Wrote an internal white paper entitled “Science and Technology Engagement Analysis: Opportunity Costs of Non-CRADA Work for Others Contracts at the National Renewable Energy Laboratory” detailing the the cost-benefits of substituting ROI monetization and income from Work for Others contracts.

University of Illinois Chicago | Sep 2009 - May 2011

Lecturer / Adjunct Professor

Taught courses in Intermediate Microeconomics, and Price Theory

My Education

Take a look at my formal education

MA, EconomicsUniversity of Illinois at Chicago | 2010

BA, Business and Economics, Mathematics MinorBenedictine University | 2008

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