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About Me
I’m Frank – a data engineer and applied AI builder focused on making complex systems reliable, scalable and genuinely useful. I’ve architected high-volume Spark and Databricks pipelines, designed cloud-native platforms across AWS and Azure, and delivered millions in modeled savings for enterprise data teams. Recently, my work has centered on the emerging stack around GenAI and Model Context Protocol (MCP), where I explore how LLMs reshape workflows, data engineering patterns, and real-world decision systems. If you’re interested in robust data platforms, production AI, or the future of intelligent tooling, you’re in the right place.
Software engineer and data whisperer who makes your data work for you


We talk a lot about process—not outcome—and trying to consistently take all the best information you can and consistently make good decisions. Sometimes they work and sometimes they don’t, but you reevaluate them all.

- Sam Hinkie, architect of the “Trust the Process” 76ers (Source: Bleacher Report)

Biography

I am a seasoned software engineer with a love of data in all forms with a goal of making data useful. Data is the most valuable asset class of the 21st century with the ability to inform strategy and create understanding. The ability to utilize, monetize and ultimately extract value from data is both key to modern infrastructure and the apple of my eye. I have been blessed to experience and develop all stages of the data lifecycle from data capture to end-user reporting. Check out my resume!

I was previously a senior data engineer at Axis Group LLC specializing in machine learning, non-standard systems architecture and data ingestion. I specialized in making data useful and understandable for my clients. During my time at Axis, I positioned myself as a Swiss army knife with a proven track record of learning new frameworks quickly to best serve my clients.

For more specific information about me feel free to explore the pages listed above or contact me!

Experience

The below section indicates the full timeline of my employment from the age of 16 until the present day. Please refer to my LinkedIn profile for a more targeted summary of my relevant professional experience or examine my resume!

Kovacs Data Works: Hoboken, NJ

Senior Platform Engineer (August 2025 - Present)

Axis Group: Atlanta, GA (Remote)

Senior Data Engineer (January 2025 - July 2025)

Data Engineer (April 2022 - December 2024)

Associate Data Engineer (September 2021 - April 2022)

Carnegie Mellon Department of Statistics & Data Science

Graduate Teaching Assistant (August 2019 - May 2021)

IT Associate (May 2017 - August 2017)

Undergraduate Teaching Assistant (January 2017 - May 2019)

Carnegie Mellon Student Life

Community Advisor (August 2018 - May 2019)

Resident Assistant (August 2016 - May 2018)

West Essex YMCA

Camp Counselor (June 2015 - July 2016, June 2019 - August 2019)

Equipment Manager (June 2013 - August 2014)

Education

Carnegie Mellon University (August 2015 - May 2021)

Both degrees were attained from the Department of Statistics and Data Science at Carnegie Mellon University.

Master’s of Statistical Practice (2021)

My university research centered on the effectiveness of mask mandates in spurring mask compliance and prevalence of Covid-19 in communities. I worked with Dr. Alex Reinhart using data from Carnegie Mellon’s Delphi Group and the University of Washington’s Covid-19 State Policy Group to quantify the marginal effect of county and state-level mask mandates. Earlier research focused on the development of a modern statistical learning tool in conjunction with Dr. Philipp Burckhardt under the supervision of Dr. Rebecca Nugent. The tool, ISLE, tracks student progress while making data science interactive at all stages of the development lifecycle.

Relevant Coursework
  • 36-661: Special Topics in Epidemiology
  • 36-617: Applied Linear Models
  • 36-668: Text Analysis
  • 36-700: PhD Probability
  • 36-618: Time Series
  • 36-726: Statistical Practice
Projects
  • Corporate Capstone
    • Project in progress as part of 36-726: Statistical Practice

  • Independent Study: Delphi CovidCAST Modeling
    • An Examination of Interrupted Time Series to Quantify the Effectiveness of Covid-19 Preventative Mandates
Teaching
  • Fall 2020 - Present: 36-200 - Reasoning with Data
    • Taught weekly recitation sections
    • Held weekly office hours to answer student questions

  • Fall 2019: 36-750 - PhD Statistical Computing
    • Assisted with in-class activities during each lecture
    • Graded homework assignments through Git for both correctness and professional style
Awards & Honors
  • 2021 Outstanding Masters Teaching Assistant
  • Statistical Practice Scholarship

B.S. in Statistics and Machine Learning (2019)

I received my BS in Statistics and Machine Learning from Carnegie Mellon University in 2019. During my time as an undergrad, I was heavily involved in the development and implementation of 36-200, the first-semester introductory statistics course using ISLE.

Relevant Coursework
  • 10-601: Machine Learning (Masters)
  • 36-461: Data Mining
  • 36-650: PhD Statistical Computing
  • 36-651: Advanced Statistical Computing
  • 36-495: Undergraduate Research
  • 36-401: Modern Regression
  • 15-122: Principles of Imperative Programming
  • 21-301: Combinatorics
  • 21-355: Real Analysis I
  • 15-351: Algorithms and Data Structures
Projects
Teaching

Additionally I was active in residence life as a resident assistant for two years and a head RA during my senior year managing a team of 10 RAs and 300 first year residents.

Awards & Honors
  • 2018 Undergraduate Teaching Assistant of the Year
  • 2018 Meeting of the Minds Statistics Poster - First Place
  • Senior Leadership Award

Seton Hall Preparatory School (2011 - 2015)

  • National Merit Commendation
  • Medallion for Excellence in Statistics