Scott Clark

CV

Long-form curriculum vitae. The short version lives on the home page. Downloadable PDFs: two-page resume and the longer academic CV. Full LaTeX source and a structured markdown profile are in github.com/sc932/resume.

Experience

  1. 2023 — present
    Distributional Co-founder & CEO
    • Analytics for AI agents — discovering behavioral signals in agent trace data for continuous AI reliability. 30-person team, $30M raised (Seed Dec 2023 led by Andreessen Horowitz; Series A Oct 2024 led by Two Sigma Ventures).
    • Co-founders: Michael McCourt (CTO; multi-paper SigOpt-era co-author), David Rosales (COO), Nick Payton (CRO). 11-person founding team sourced from Bloomberg, Google, Meta, Intel, SigOpt, Slack, Stripe, Uber, Yelp.
    • Product evolved 2023–2025 from pre-deployment AI-testing to production behavioral analytics for AI agents — turning raw trace data into actionable insights for AI teams.
    • US Patent 12,505,027 (2025, named inventor): anomaly detection in deployed AI applications.
  2. 2020 — 2023
    Intel VP & GM, AI/HPC Supercomputing
    • Joined Intel through the acquisition of SigOpt (Oct 2020). Led a multi-disciplinary ~200-person organization responsible for application-level AI and HPC software within Intel's Supercomputing Group.
    • Title progression: Director & GM of SigOpt (Nov 2020 – Mar 2021) → Senior Director & GM of SigOpt and AI Application Enablement (Mar 2021 – Sep 2022) → VP & GM of AI and HPC Supercomputing Application Level Engineering (Sep 2022 – Jun 2023).
    • Public face for Intel's oneAPI open-ecosystem thesis — SC22 theCUBE panel (Dallas, Nov 2022), MLconf 2021 Webinar, Ai4 2021, Intel Conversations in the Cloud Ep. 250.
    • Integrated SigOpt's IP into Intel's AI Analytics Toolkit; recognized as a leader in AI Software Optimization (Kisaco Research Leadership Council, 2021).
  3. 2014 — 2020
    SigOpt Co-founder & CEO
    • Commercial Bayesian-optimization platform serving Fortune 500 enterprises in finance, trading, intelligence, and technology. Acquired by Intel (Oct 29, 2020).
    • Raised $17M across seed + Series A + Series A+ + strategic rounds: Andreessen Horowitz (led seed 2015 and A 2016); Blumberg Capital (lead, 2018 Series A+, with Two Sigma Investments co-investing, announced 2019); Data Collective (DCVC), SV Angel, Stanford, In-Q-Tel strategic, Y Combinator (W15), and notable angels.
    • Co-founders: Patrick Hayes (CTO 2014–2021), Eric Liu.
    • Grew from Y Combinator W15 through Series A+ with customers in algorithmic trading, government/intelligence, enterprise AI, and consumer-tech.
    • Awards: Gartner Cool Vendor in AI Core Technologies (2017); Barclays Open Innovation Challenge winner (2017); Kisaco Research KLC Leader (2021).
    • Drove research culture and IP: 15 peer-reviewed papers + ~20 granted US patents as named inventor across Intelligent Optimization Platform, Multi-Criteria Optimization, and Multi-Solution Hyperparameter Tuning families.
  4. 2012 — 2014
    Yelp Software Engineer & Team Lead, Ad Targeting
    • Optimization: Co-developed and led team for MOE (Metric Optimization Engine, github.com/Yelp/MOE) — first production Bayesian-optimization open-source package. Third-most-popular Yelp open-source release within 72 hours of launch; basis of SigOpt's founding.
    • Ad targeting: Implemented multi-armed bandit strategies for ad selection, sole targeting engineer on mobile ads rollout, developed location-based targeting algorithms.
    • Director, Yelp Dataset Challenge: created, implemented, and directed yelp.com/dataset_challenge; used by 100,000+ students worldwide since its inception.
    • Leadership: Founded Yelp's internal Applied Learning Group (bi-weekly all-engineering speaker series); MOE team lead; intern and new-hire mentor; 200+ technical interviews.
    • Featured in the Wall Street Journal, Aug 8 2014 (Elizabeth Dwoskin, “Big Data's High-Priests of Algorithms”) and the Cornell ORIE alumni spotlight (2014).
  5. May — Aug 2011
    Bloomberg LP Financial Software Development Intern
    • Developed end-to-end portfolio-analytics function in C++ and JavaScript (concept → back-end integration → GUI → PDF reporting).

Education

  1. 2008 — 2012
    Cornell University Ph.D. Applied Mathematics, M.S. Computer Science

    Department of Energy Computational Science Graduate Fellow (full four-year scholarship). Dissertation: "Parallel Machine Learning Algorithms in Bioinformatics and Global Optimization." Advisor: Peter Frazier. Committee: Steve Strogatz, Bart Selman. DOE practicums at Los Alamos National Laboratory and the Joint Genome Institute (LBNL).

  2. 2004 — 2008
    Oregon State University B.Sc. Mathematics, B.Sc. Computational Physics, B.Sc. Physics

    Triple bachelor's degrees in four years, magna cum laude. Minors in Actuarial Sciences and Mathematical Sciences. Paradigms in Physics degree track. NSF REU summers at UC Davis (computational biophysics) and the Max Planck Institute Dresden (extreme-value statistics of chaotic quantum systems).

Research Experience

  1. May — Aug 2010
    DOE Joint Genome Institute (LBNL) DOE CSGF Practicum under Dr. Zhong Wang & Rob Egan
    • Built open-source genome-assembly validation framework (ALE, published Bioinformatics 2013, 208 cites).
  2. May — Aug 2009
    Los Alamos National Laboratory DOE CSGF Practicum under Drs. Nick Hengartner & Joel Berendzen
    • Metagenomics / local sequence-alignment algorithms in Python, C, and CUDA (Velvetrope). This practicum pivoted my dissertation from computational fluid dynamics to bioinformatics.
  3. May — Aug 2007
    Max Planck Institute for the Physics of Complex Systems NSF REU under Prof. Steven Tomsovic (WSU)
    • Extreme-value statistics of chaotic quantum systems in MATLAB and FORTRAN.
  4. May — Aug 2006
    University of California, Davis NSF REU under Prof. Daniel Cox
    • Computational biophysics / protein folding in Java. Results published in Prion (2008).

Awards & Honors

  1. 2016
    Forbes 30 Under 30

    Enterprise Technology category. Recognized as co-founder & CEO of SigOpt.

  2. 2016
    Young Alumni Award

    Oregon State University, College of Science.

  3. 2010
    DOE CSGF Communicating Science Award (Honorable Mention)

    For the essay "Solving Genomic Jigsaws," DEIXIS Magazine.

  4. 2008 — 2012
    DOE Computational Science Graduate Fellowship

    Full four-year PhD scholarship (~$300,000), Department of Energy. Contract DE-FG02-97ER25308.

  5. 2008
    Cornell University Sage Fellowship

    $55,000, declined in favor of DOE CSGF.

  6. 2010 — 2012
    NERSC Production + Startup Allocations

    Principal Investigator, Cray XT4 (DOE Contract DE-AC02-05CH11231), 100,000 production hours plus startup renewals.

Board & Advisory

  1. 2022 — 2025
    Oregon Museum of Science and Industry Board of Trustees · Treasurer · Finance Committee Chair

    Executive Committee member; chaired the Finance Committee through OMSI's post-COVID financial recovery.

  2. 2019 — 2025
    Oregon State University, College of Science Board of Advisors

    Advised the Dean's office on industry partnerships and research-to-product translation.

  3. 2018 — 2025
    Oregon State University, College of Science Industry and Innovation Council

    Industry-side member supporting the College's translational research initiatives.

Research Areas

Bayesian optimization · Gaussian processes · Optimal learning · Multi-armed bandits · Hyperparameter tuning · AI reliability · AI testing & evaluation · Production ML observability · LLM and agent evaluation · Experiment design · A/B testing · Monte Carlo methods · Numerical analysis · High-performance computing · Parallel algorithms · Distributed systems · CUDA / GPU computing · Bioinformatics · Genome assembly · Computational biophysics

Selected Publications

  1. 2020
    Parallel Bayesian Global Optimization of Expensive Functions Operations Research

    Wang, Clark, Liu, Frazier. 263+ citations. Theoretical and practical algorithms for parallel evaluation in BO.

  2. 2013
    ALE: A Generic Assembly Likelihood Evaluation Framework Bioinformatics

    Clark, Egan, Frazier, Wang. 208+ citations. Reference-free quality metric for genome assemblies. Output of the JGI 2010 DOE practicum.

  3. 2016
    Bayesian Optimization for Machine Learning: A Practical Guidebook arXiv:1612.04858

    Dewancker, McCourt, Clark. 142+ citations. Widely-cited practitioner guide; the most-read public artifact from the SigOpt research program.

  4. 2025
    Anomaly Detection in Deployed Artificial Intelligence Applications U.S. Patent 12,505,027

    Distributional's first granted patent. McCourt, Bourassa-Denis, Laban, Kim, Dewancker, Cheng, Clark.

Full publication list and abstracts on the Research page; the most up-to-date list is on Google Scholar (1,200+ citations, h-index 16).

Selected Talks & Podcasts

  1. Mar 2026
    AI Reliability for the Enterprise SAIR Podcast
  2. May 2025
    Behavioral Analytics for Production AI AI + a16z Podcast (with Matt Bornstein)
  3. Nov 2022
    oneAPI and the Future of Accelerated Computing SC22 theCUBE Panel (with David Schmidt of Dell)
  4. Mar 2019
    Tuning the Untunable NVIDIA GTC Silicon Valley
  5. Dec 2019
    From argmax f(x) to an International Business Cornell CAM Notable Alumni Speaker Series

40+ documented appearances since 2013. Full list on the Talks page.