Muhammet Furkan Karakaya

Data scientist, quantitative researcher, computational social scientist with a PhD, and data engineering and AI developer.

I turn large, messy, multi-source data into measures and models people can trust. My doctoral research used large language models to measure how closely political candidates' posts match their party platforms. Today I build data pipelines and AI services at Foxconn Industrial Internet.

Now
Software Developer, Data Engineering & AI at Foxconn Industrial Internet
PhD
Political Science, Binghamton University, 2026
Focus
NLP, causal inference and data engineering

About

Six-plus years of statistics, coding and applied research, from a PhD to industry.

I am a data scientist and quantitative researcher with a PhD in political science from Binghamton University and 6+ years of experience in statistics, coding and applied computational research.

During my PhD I developed the Ideological Congruence Score (ICS), a text analysis method that uses large language model embeddings to measure how closely candidates' social media posts align with their party platforms. I built the whole pipeline myself, from collecting and preprocessing millions of posts to embedding, similarity scoring and validation, and applied it to U.S. House elections and to Turkey. You can read about it under research.

While studying, I worked as a data science consultant for the Graduate School, advising 50+ projects each semester for graduate students in engineering, the natural sciences and the social sciences, and I collaborated with faculty in public policy, health sciences and education on peer-reviewed publications.

At Foxconn Industrial Internet I work on data engineering and AI: automated pipelines and dashboards for teams in four countries, an on-premise LLM service, and the Linux, Windows and container infrastructure they run on. Details are in my experience and CV.

Skills

Statistics and causal inference

  • Causal inference
  • Difference-in-differences
  • Synthetic control
  • Natural experiments
  • Multilevel models
  • Panel data
  • Time series and forecasting
  • Maximum likelihood

Machine learning, NLP and AI

  • LLM embeddings
  • Sentence transformers
  • Semantic similarity
  • Text classification
  • Sentiment analysis
  • Random forest
  • Gradient boosting
  • Clustering
  • Neural networks
  • Prompt engineering
  • LLM-assisted workflows
  • On-premise LLM services

Data engineering

  • ETL/ELT pipelines
  • Multi-source integration
  • Deduplication and entity resolution
  • Data-quality checks
  • Drift detection
  • Automated dashboards
  • API data integration
  • Web scraping

Systems and DevOps

  • Docker
  • Kubernetes
  • Linux server administration
  • Windows Server
  • macOS
  • Bash and shell scripting
  • PowerShell
  • Git and GitHub
  • Containerized services
  • System design

Languages and tools

  • Python
  • R
  • SQL
  • STATA
  • SPSS
  • SAS
  • JavaScript
  • HTML
  • LaTeX
  • Tableau
  • Power BI

Research design and UX

  • Survey design
  • Survey experiments
  • A/B testing
  • UX research
  • Mixed methods
  • Data storytelling

Experience

Industry, consulting, research and teaching.

  1. Software Developer, Data Engineering & AI

    Foxconn Industrial Internet

    • Jan 2026 – Present
    • Mount Pleasant, WI
    • Build and automate Python data pipelines and dashboards that IT teams in the US, Taiwan, China and India use every day; automation cut the team's reporting time by 45%.
    • Redefined how key metrics are counted after finding a headline figure inflated nearly threefold, and built a deduplicated, time-aware dataset of 300,000+ records with drift detection.
    • Designed and deployed an on-premise AI service that brings LLM-assisted workflows to office users within enterprise data-security constraints.
    • Design and run containerized services with Docker and Kubernetes on hardened Linux and Windows servers.
  2. Data Science Consultant

    Binghamton University, Graduate School

    • Jan 2022 – Dec 2025
    • Binghamton, NY
    • Advised 50+ graduate students each semester, across engineering, the natural sciences and the social sciences, on statistical modeling, machine learning, causal inference and coding in Python and R.
    • Scoped ambiguous research problems into tractable analysis plans, executed or guided the analysis, and presented results to non-technical audiences.
    • Designed and delivered department-wide workshops on Python, R, statistical project design and reproducible analysis.
  3. Research Assistant, Public Policy, Health Sciences and Education

    Binghamton University

    • Jan 2021 – May 2025
    • Binghamton, NY
    • Analyzed large-scale survey data with STATA, R and Python for faculty research on online tax and fee payment systems and on student mental health and diet, and conducted a systematic literature review on autism diagnosis.
    • Built automated data cleaning and analysis pipelines and co-authored peer-reviewed publications.
  4. Lecturer, PLSC 398: Social Data Analytics Using Python

    Binghamton University, Political Science Department

    • Dec 2024 – Jan 2025
    • Binghamton, NY
    • Designed and taught an undergraduate course on cleaning, visualizing and modeling structured and unstructured data in Python.
  5. Data Analyst

    Binghamton University, Student Affairs Assessment

    • Jan 2024 – Oct 2024
    • Binghamton, NY
    • Built ETL pipelines that integrate multi-source institutional data, and automated dashboards in R and Python for administrative planning.

Research

Measuring party cohesion with language models, plus applied work in public policy and health.

My dissertation, A Computational Approach to Party Cohesion: When Do Parties Use the Broad-Appeal Strategy in Different Party Systems?, introduces the Ideological Congruence Score and applies it to the United States and Turkey. The papers below develop its chapters. Citations are on Google Scholar.

Working papers

Examining the Evolution of Online Tax and Fee Payment Systems

Jones, P. A., Karakaya, M. F., & Reitano, V.

Under review, International Journal of Public Administration

Read the abstractHide the abstract

Subnational governments around the world collect property taxes and user fees through digital and non-digital methods... Collectively, these findings provide evidence for governments adopting digital innovations that benefit citizens and public service provision.

Effects of Co-ethnic Terrorism on Ethnic Voting: Kurdish Voters in Turkey

Karakaya, M. F.

Working paper

Party Vote Share and Cost of Voting: The 2020 House of Representatives Election

Karakaya, M. F.

Working paper

Published articles

A Systematic Literature Review of Racial Disproportionality in Autism in the US

Kim, H., Karakaya, M. F., Skinner, M., & Baker, D.

Journal of Autism and Developmental Disorders, 55(3), 1010–1030, 2025

Read the abstractHide the abstract

In recent years, the Autism and Developmental Disabilities Monitoring Network has observed a shift in racial disparities in autism... These findings prompt a closer look into the causes and implications of these disparities, offering the underlying issues within the current diagnostic system and highlighting the need for further research to ensure equal educational opportunities regardless of disabilities and race/ethnicity.

Dental Anxiety and Its Association with Dietary Intake and Food Groups

Begdache, L., Ahmed, E., Malik, S., & Karakaya, M. F.

Dentistry Journal, 11(10), 240, 2023

Read the abstractHide the abstract

Although there is an established connection between diet and mental health, the relationship between diet and dental anxiety has not been examined yet... This cross-sectional study provides proof of concept that dietary patterns are potentially associated with dental anxiety.