# Scott Clark — Curriculum Vitae

Long-form CV. The short version lives on the home page (https://scottclark.io/). Downloadable PDFs: [two-page resume](https://scottclark.io/resume/scott-clark-resume.pdf) and the longer [academic CV](https://scottclark.io/resume/scott-clark-cv.pdf). Full LaTeX source and a structured markdown profile are at https://github.com/sc932/resume.

## Experience

### 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.

### 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).

### 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.

### 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).

### 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

### 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).

### 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

### 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).

### 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.

### 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.

### 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

### 2016 · Forbes 30 Under 30

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

### 2016 · Young Alumni Award

Oregon State University, College of Science.

### 2010 · DOE CSGF Communicating Science Award (Honorable Mention)

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

### 2008 — 2012 · DOE Computational Science Graduate Fellowship

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

### 2008 · Cornell University Sage Fellowship

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

### 2010 — 2012 · NERSC Production + Startup Allocations

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

## Board & Advisory

### 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.

### 2019 — 2025 · Oregon State University, College of Science · Board of Advisors

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

### 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

### 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.

### 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.

### 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.

### 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: https://scottclark.io/publications (1,200+ citations, h-index 16; Google Scholar: https://scholar.google.com/citations?user=mwWbhAUAAAAJ)

## Selected Talks & Podcasts

### Mar 2026 · AI Reliability for the Enterprise

*SAIR Podcast*

### May 2025 · Behavioral Analytics for Production AI

*AI + a16z Podcast (with Matt Bornstein)*

### Nov 2022 · oneAPI and the Future of Accelerated Computing

*SC22 theCUBE Panel (with David Schmidt of Dell)*

### Mar 2019 · Tuning the Untunable

*NVIDIA GTC Silicon Valley*

### Dec 2019 · From argmax f(x) to an International Business

*Cornell CAM Notable Alumni Speaker Series*

Full talks/podcasts list (40+ appearances since 2013): https://scottclark.io/talks

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Source: https://scottclark.io/cv