J.P. Morgan

Data Scientist - Senior Associate, Research and Applied Machine Learning, Aumni

University of Utah - David Eccles School of Business

• Solo lecture FINAN6520 - "Intro to Financial Programming", a course built to help students harness the power of Python and system development skills by building applications focused on finance domains. 
• Co-lecture FINAN6500 - “Financial Modeling with Python", a course focused on traditional/modern financial modeling techniques related to equities, options, fixed-income, and more.
• Manage all code repositories and development of new materials.

Adjunct Instructor

• Develop python learning materials to handle a large array of financial modeling methods.
• Assist in the construction and administration of a graduate level python course.
• Maintain Git repositories of all associated course materials.

Associate Instructor | (Co-Lecturer)

Aumni

• Participate in research initiatives related to data product development, data fidelity, and ad-hoc analysis.
• Develop predictive models using machine learning and classical statistical methods for the development of proprietary data products.
• Assist in the development of MLops infrastructure for productionized model servicing.

Acquired by JPMC May 2023.

Data Scientist, Research and Applied Machine Learning

National Trust for Local News

Primarily focused on minimizing acquisition/investment risk and providing measurable impact through R&D processes.

• Led in development of a quantitative decision framework to rank acquisition targets.
• Analyzed demographic, economic, “social resource”, and civic data in multiple US regions as well as analysis of 50 states and 3100+ counties in the United States.
• Collaborated with co-researchers to relate publication context variables to region related variables. 
• Provided financial modeling assistance for acquisition target valuation. 
• Assisted in the recommendation of $1M+ worth of acquisition targets. 
• Developed a full-stack web-application used to prioritize media organizations of interest and aggregate business logic/data into a single source of information for the organization.

Business Intelligence Engineer

Sorenson Impact

Sr. Data Science Fellow

• Visualize, interpret, report, and communicate data findings creatively in a various formats
• Condense large and complex data sets into clear, concise, easy-to-understand observations
• Facilitate preliminary analysis for model development and implementation
• Identify business problems and create data enabled solutions

Data Science Fellow

ClearRTB

• Analyze data with statistical methods, interpret results, and provide reporting.
• Research, design, develop, implement, and quantitative decision-science models.
• Contribute to the measurement of robotic ad-traffic which yielded the reclassification of 2 million misclassified data points.
• Implement A/B testing related to programmatic ad-placements on pseudo-web pages analyzed by Amazon Mechanical Turk workers.

Data Scientist Intern

Project Embrace

• Planning and monitoring of day-to-day device management
• Manage the upkeep and improvement of donated devices and storage facilities
• Ensure quality control parameters for donated devices
• Oversee the flow of devices in and out of storage facilities
• Coordinate logistics related to local and global campaigns
• Research and implementation of new business logistics practices

Operations Manager

• Maintain overall financial health and implement of realistic budget outlines
• Oversight of the flow of cash and financial instruments
• Administer project feasibility analysis upon new opportunities and investments
• Create financial reports monthly, quarterly, and yearly
• Develop practices that ensure low cost and risk related to operations
• Understand and adhere to financial regulations and legislation

Head of Finance

• Oversaw and coordinated the transition of analog data management to cloud based organizational systems
• Developed from scratch a full-stack web-application to manage inventory data and dashboards
• Iterated upon system by adding organizational Knowledge Base, CRM, and automated reporting tools
• Established internal engineering department by sourcing and hiring 3 developers and cyber security professionals

Software Engineer

Kinkade is a talented programmer who enjoys creating full-stack web-applications, websites, quantitative financial models, and all things python. He has an extensive experience in developing tools in the realms of social benefit non-profit, academia, quantitative investing, and business services. Kinkade enjoys solving complex problems and coming up with actionable insights from data analysis. 

Kinkade also loves the opportunity to educate others. Currently, he is co-lecturing a financial programming course at the David Eccles School of Business. Kinkade assisted in the development of the course and provides advisement on the continued improvement and alteration of course material.

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