About matt
I am a highly-motivated, detail-oriented and creative data scientist with over 10 years of related experience, who enjoys solving complex problems using analytical methods. Throughout my career, I have been passionate about the pursuit of elegant solutions to difficult business problems. In my current role as a Data Scientist at KPMG Ignition, I build and deploy machine learning models that augment the workflows of our tax professionals, with a focus on scalability and automation. I currently program using Python on a daily basis, and have extensive experience telling data-centric stories and communicating data-driven insights to leaders and other cross-functional team members. To accomplish all this, I have expert level skills in both Python and SQL, and have extensively used Python’s open-source ML ecosystem, as well as cloud-based tools such as Azure and Azure Machine Learning. My abilities as a Data Scientist are rooted in a robust education in mathematics, programming, critical thinking, and problem solving. I began with a bachelor's degree in Electrical Engineering from the Colorado School of Mines. I followed that with a master's degree in Engineering and Technology Management from Mines as well, with a focus on operations research and data science. Striving to continue my education, I completed the Data Science Immersive at Galvanize in Denver, where I honed my machine learning, data science, data visualization, and data engineering skills even further. I attribute my success within data science in large part to this extensive and in-depth analytical education. Prior to KPMG, I was a Consultant in PA Consulting Group’s Global Energy and Utilities Practice, and have ten years of data-driven energy industry experience. My primary energy expertise includes power market modeling and analytics, power generation asset valuation, and mergers and acquisition advisory support. I helped conduct hundreds of market power price forecasts during my time at PA, and those forecasts have been used to support power plant financing, transactions, client strategy, and bid development. I have extensive experience running large-scale power market modeling simulation software, as well stochastic power plant dispatch optimization tools. In my free time, I very much enjoy running, hiking, snowboarding, going to concerts (hopefully again soon), and playing the guitar and drums. I am a Colorado native, originally from a small town on the Western Slope called Montrose, and currently reside in Denver, CO. Please feel free to reach out to me any time!
Key Skills
Experience
Natural Language Processing Engineer
CurrentPinnacol Assurance
Senior Associate - Machine Learning And Data Science
Kpmg
In my current role as a Data Scientist at KPMG Ignition, I build and deploy cloud-based machine learning models and pipelines, with a focus on scalability and automation. Throughout my time at KPMG, I have focused on: Automating pipelines incorporating training, retraining, and deployment of ML models using cloud-based tools such as Azure ML. Collaborating effectively on cross-functional teams with business leaders, developers, and subject matter experts, to create client-facing web apps utilizing ML models. Communicating the value of data science, and clearly explaining complex ML concepts across teams and to upper-level management. I currently program using Python on a daily basis, and have extensive experience telling data-centric stories and communicating model-based insights to leaders and other team members. To accomplish all this, I have expert level skills in both Python and SQL, and have extensively used Python’s open-source ML ecosystem, as well as cloud providers such as Azure, and have an expert-level skillset with respect to using Azure Machine Learning and other Azure resources. I am also the leader of the Denver Ignition Data Science team, and focus on educating other team members about complex machine learning and data science concepts and use cases. I am constantly searching for new potential applications for ML-based solutions, and approach business problems with empirical data-driven solutions in mind.
Consultant
Pa Consulting
Energy market modeling and data analytics expert with a background in power price forecasting, power asset modeling and power market analytics. Energy Market Analysis – Conducted and optimized energy market analysis using AURORAxmp market modeling software, analyzed results of electric market models, determined validity of model outputs, conducted due diligence to make sure models were up to date with latest energy and commodity market movements, analyzed large data sets and created individual Excel models depending on project needs. Power Asset Valuation – For buy-side and sell-side M&A support, simulated operations of hundreds of mid-merit and peaking power plants using a stochastic dispatch optimization model, used the results of this model and other internal proprietary PA models to create cash flow pro formas. Involved in the valuation of more than $20 billion of power generating assets. Prepare Client Deliverables – Created client-facing Excel, Word, and PowerPoint documents combining analysis of energy markets, asset specific dispatch results, and cash flow pro formas into succinct and valuable takeaways.
Education
Galvanize
Colorado School Of Mines
Masters
Colorado School Of Mines
Bachelors
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Common Questions
What is matt's expertise?
matt specializes in NLP Engineer, with expertise in algorithms, analytics, big data, business analytics, business strategy.
Where is matt located?
matt is based in denver, colorado, united states.
How much experience does matt have?
matt has 21+ years of professional experience.
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