Applied AI,
engineered for impact

Evan is a serial problem solver with deep expertise in AI. He has a proven history of leading cross-functional teams to transform messy, real-world data into measurable impact—from zero-to-one prototyping to global-scale production deployments. Prior to co-founding Kiso, Evan was a machine learning engineer at Stripe, where he developed multimodal deep learning models to combat fraud. He was formerly on the research team of Vicarious, an AI startup acquired by Alphabet/DeepMind in 2022.

Sam is highly skilled in translating complex business challenges into elegant technical solutions that actually work. He has a track record of bringing together exceptional teams that solve problems at the intersection of operations research and ML/AI. Before co-founding Kiso, Sam developed Flexport's “Boat Assignment Engine” planning system and Stitch Fix's last-mile delivery assignment algorithm, which both delivered millions in annual savings.

Brian is an experienced leader in machine learning, operations research, and data science—skilled in crafting data strategy, building high-performing teams, and delivering impactful solutions. He is also a talented designer of data visualizations and the creator of the Stitch Fix Algorithms Tour. He has a previous career as a distinguished researcher in the field of advanced controls for building systems.

Sitki is a data science leader who has overseen the development of critical operational solutions used by the world’s largest automotive, cosmetics, grocery, and high-tech companies. He has extensive experience scaling technical teams from the ground up, bringing together world-class talent in Data Science and Optimization. He created and led the operations algorithms team at Stitch Fix, with a dual focus on cross-functional financial planning and order-to-delivery execution.

Colin has had a prolific career bringing advanced data science to some of the largest brands in the technology, semiconductor, automotive, CPG, consumer electronics, life sciences, and retail industries. He previously founded End-to-End Analytics, which was acquired by Accenture in 2020. Colin was also Operations Management faculty at the University of Michigan Ross School of Business, as well as a lecturer at the Stanford Graduate School of Business, Stanford School of Engineering, and the Berkeley Haas School of Business.

Rafael has extensive experience in applying algorithmic solutions to business problems across a wide range of sectors. His industry experience includes retail, technology, semiconductors, and consumer electronics, while his functional experience ranges from demand forecasting and inventory optimization to network design and capacity planning.

Jacqueline has a technical background in machine learning and AI, in addition to deep consulting experience across a wide range of industries. She was previously the lead data scientist at Clear.bio, a health tech startup building personal food recommendations based on biomarkers. She was also the tech lead for a data science team at the Port of Rotterdam, the largest port in Europe, where her contributions drove $1M+ cost reductions in dredging and catalyzed new company-wide standards for productionizing machine learning applications.

Adam has deep experience using optimization and AI to solve real-world decision problems. At Uber, Adam built and optimized systems at the core of Uber’s marketplace, balancing real-time supply and demand. Previously, Adam worked on the quantitative models powering Wealthfront's personal finance products.

Steve is a technical expert with a background in data science and optimization. He builds solutions to address complex business problems from the ground up, with experience across the retail, semiconductor manufacturing, and high-tech industries. His past work includes DTC fulfillment optimization, inventory optimization, and leading a team to productionize and deploy an algorithmic inventory planning system.

Douglas has over 20 years of experience building software to model complex systems in supply chain operations, retail planning, and astrophysics. His work combines machine learning, optimization, and simulation to manage competing business objectives and drive impact through algorithmic decision systems. Douglas is an alumni member of the Institute for Advanced Study and of the Insight Data Science post-doctoral program.

Will is a product leader with a background in software engineering and engineering management. He helps teams ship impactful products, fast. As the first product manager at Census, he launched a new offering that became a major revenue driver. At Flexport, Will built the foundational technology that powered the ocean freight business as it scaled 200x over four years.

Jared is an AI and engineering leader with a proven track record of building high-performing teams and production-grade AI systems. With a focus on scalability, Jared has built AI-driven teams, tooling, infrastructure, experimentation frameworks, and products—from highly regulated, performance-critical domains (aerospace, energy, and financial technology) to fast-moving consumer-facing technologies (e-commerce, search, recommendations).

Sergei is a data and decision science leader with experience building high-performing teams and delivering analytics strategies that drive real-world impact. His work spans hyperscalers, semiconductors, and FMCG, with a focus on supply chain planning, simulation, and AI adoption. He pairs creative problem solving with structured thinking to navigate complex systems.

Brent is a versatile engineering and decision-science leader who turns complex, data-rich operations into scalable products. He has led 15-person teams shipping optimization and AI systems that power Stitch Fix’s fulfillment network, unlocking a 5% annual revenue lift for the company, and previously scaled Included Health’s recommendation engine and GE Digital’s industrial ML platform.

Karl is a data science leader who has led high-impact projects in a multitude of industries. He shapes strategy with advanced modeling, optimization, and scalable solutions that put self-service insights into decision-makers’ hands. He pairs rigorous data science with clear communication to outline, realize, and sustain lasting impact.

Liam is an applied scientist and management consultant with expertise in using optimization and machine learning to create value for core business operations. He has worked across a range of industries, including mining, rail transportation, manufacturing, and marketing, helping organizations translate ambiguous business problems into scalable, impact-driven technical solutions. At BCG, Liam led small cross-functional teams to deliver end-to-end digital initiatives, spanning value identification, algorithm prototyping, and MVP launch.

Steve has spent his career working with companies to design and develop state-of-the-art analytical processes to realize and sustain results. His experience spans automotive, retail, high-tech, CPG, medical devices, manufacturing, and food and beverage industries. His past work includes forecasting, demand planning, machine learning, S&OP implementation, and inventory optimization.

Ciaran is an operator with significant startup experience in a high growth environment. In his early days at Fieldwire, a construction software company, he built out processes and led teams to run the day to day operations of the company. After a successful acquisition by Hilti, Inc., he transitioned to Chief of Staff looking over major cross functional integration projects, focused on scaling operational infrastructure for Hilti’s construction software suite.

Mark is an AI research/engineering lead with 10+ years at Apple and Microsoft, where he and his teams contributed to on‑device image recognition in Photos & Memories, Apple Pay, Apple Maps, and Apple Intelligence features. At Apple he managed large data science, data engineering and ML teams as well as staying hands on with building products and models. More recently, he has been working across AI research and Applied AI on problems like reinforcement learning for custom LLMs, models for computer-use and browser automation, and tools for private and personal AI.

Jorg is a data leader with extensive experience building high-performing teams that deliver production-grade machine learning and strategic analytics. He has scaled data organizations from the ground up—growing teams from 2 to 50+ people and helped develop algorithms that drive measurable business impact both as an individual contributor and people manager: from shipping and allocation optimization at Stitch Fix, building subscriber personalization at Rent the Runway to strategic work on pricing and positioning at Chief.

Torin has led dozens of technology projects in the supply chain space. He specializes in the end-to-end development of capabilities including analytical discovery, business process design, and software development. His prior work at places like Accenture and McKinsey in the high-tech and retail industries has helped clients change the way they approach supply chain planning and operations.

Aga is a technical leader at the intersection of AI, engineering, and data science, with over 10 years of experience taking ambiguous problems from -1 to 1 and scaling them into production-grade systems. She pairs strong product judgment with deep systems expertise, building robust data foundations and reliable ML capabilities across personalization and modern AI. At Stitch Fix, she drove some of the earliest industry adoption of GPT-2/LLM capabilities well before ChatGPT became widely known. She later led Data Science & Engineering at Bain Capital Ventures. A South Park Commons alumna, she is a startup builder combining strategy with hands-on execution.