Adam DeJans Jr.

About Me

Applied operations research scientist with over a decade of experience designing and deploying large-scale optimization and simulation systems in production environments. Former D1 student-athlete turned mathematician turned decision scientist — with a contrarian, practitioner-first approach to decisions under uncertainty.

Expertise in mixed-integer programming, stochastic modeling, decomposition methods, and algorithm design for supply chain and logistics applications. Not interested in models that live in notebooks — only systems that ship and drive real outcomes.

Led end-to-end development of decision systems impacting $60B+ in annual planning decisions, including production planning, vehicle routing, scheduling, and demand-supply matching.

Co-founder of Bit Bros LLC, where I author books, consult on decision intelligence, and design career programs for the next generation of data professionals. Former Data Content Lead at LeetCode, and advising a stealth startup in the optimization space.

Optimization

MILP, Stochastic, Decomposition, Heuristics & Metaheuristics

Published Author

4 books including best sellers in MILP Optimization

Co-Founder

Bit Bros LLC — Decision intelligence consulting & publishing

LeetCode Lead

100+ problems published, shaping AI & DS education for millions

Patent Holder

Dynamic programming-based route optimization (US20210133643A1)

Production Systems

Enterprise-grade cloud deployments at scale

Experience

Technical Account Manager

Gurobi Optimization Beaverton, OR

Aug 2025 – Present

Customer-Facing Optimization Engineering

Advanced MILP Diagnostics: Led deep technical investigations of branch-and-bound search behavior, cut generation, LP relaxations, and numerical conditioning. Identified formulation pathologies and redesigned models to reduce integrality gaps, eliminate symmetry, and improve convergence.
Algorithmic Scaling: Re-architected large-scale optimization models using decomposition, reformulation, and symmetry-breaking techniques. Enabled 2–5× instance growth while maintaining numerical stability.
Performance Engineering: Delivered 30–70% runtime reductions through structured solver tuning workflows including concurrent MIP strategies, presolve control, cut management, and memory optimization.
Optimization System Architecture: Advised engineering teams on designing scalable optimization pipelines, helping teams transition from prototype notebooks to production-grade decision systems.

Co-Founder, Author & Tech Strategist

Bit Bros LLC

Jun 2023 – Present

AI-Powered, Human-Centered Decisions

Authored the MILP Optimization Handbooks series — consistent best sellers in optimization.
Co-authored "You Got the Data Job… Now What?" — a guide to accelerating data science careers and stepping into leadership.
Consulting on decision intelligence strategy for organizations adopting optimization and AI.
Designed career programs and community learning models that help professionals transition into top roles.

LeetCode

Remote

Aug 2023 – Nov 2025

Data Content Lead

2024 – Nov 2025

AI & Data Science Education

Orchestrated world-class data content and structured learning paths for millions of developers.
Published 100+ problems and solutions in AI, data science, and algorithms, making LeetCode a go-to interview resource for AI and DS professionals.

Solution Author

Aug 2023 – 2024

Content Development

Authored high-quality solutions and editorial content for data science and algorithm problems across the platform.

Toyota North America

Plano, TX

Aug 2022 – Aug 2025

Data Science Lead, Digital Innovations

May 2025 – Aug 2025

AI Transformation & Decision Intelligence

Handpicked to lead Toyota's AI transformation across North America with a mandate to scale globally.
Architected Toyota's enterprise decision intelligence framework: integrating optimization, simulation, and probabilistic forecasting into global operations.
Championed a culture shift from data dashboards to decision-centric systems, empowering teams to act, not just analyze.

Principal Decision Scientist II

Aug 2022 – May 2025

Supply Chain & Fulfillment

Supply Allocation Optimization: Designed Toyota's North American supply allocation engine using MILP in Gurobi, directly impacting $60B in decisions and increasing production by 40,000 vehicles, yielding $390M in additional profit.
GenAI-Powered Scheduling: Integrated LLMs into production line scheduling optimizer, reducing diagnostic time by 40% and accelerating scenario analysis from hours to minutes across 15+ planners.
Automated Vehicle Ordering: Built ordering recommendation engine leveraging tree-based regression + MILP optimization, increasing profit by $64M.
Accessories Recommendation: Customer segmentation model optimizing $700M in inventory, increasing profits by $42M.

Senior AI Consultant

Infosys Consulting Lisle, IL

Sep 2021 – Aug 2022

AI & Automation

Package Delivery ETA: Designed real-time AI-driven logistics system using deep learning (TensorFlow) on Azure, processing 300M+ data points daily with a wide & deep architecture trained on billions of records.
Expedited Shipping: Developed a custom heuristic leveraging ETA predictions with real-time logistics data, cost considerations, and SLA constraints to minimize late deliveries.

Ford Motor Company

Dearborn, MI

Aug 2018 – Sep 2021

Data Scientist

2020 – Sep 2021

Autonomous Vehicles & Smart Mobility

Vehicle Fleet Simulation: Led development of a discrete event simulation tool achieving a 27% fleet size reduction while ensuring service reliability.
Vehicle Routing: Developed VRP algorithms for ride-hail, shuttle, grocery delivery, and medical transport, successfully scheduling over 300,000 trips.

Operations Research / Data Scientist

Aug 2018 – 2020

Smart Mobility & Logistics

Point-to-Point Mobility: Invented and patented a dynamic programming-based route optimization algorithm (US20210133643A1), deployed as an Android application for multimodal route planning.

AI/ML Bootcamp Instructor

Simplilearn (Caltech Partnership)

Nov 2023 – Jan 2024

Partnered with Caltech to deliver advanced AI/ML training, equipping professionals with industry-ready skills.

Software Engineer & Data Analyst

Marposs Corporation Auburn Hills, MI

Feb 2017 – Aug 2018

Automated Report Generation: Developed a text-mining automation tool using Python (NLTK, Pandas, Flask), reducing manual report generation time by 30%.

Mathematics Lecturer

Oakland University Rochester, MI

Sep 2016 – May 2018

Taught mathematics courses while pursuing M.Sc. in Industrial Applied Mathematics.

Books & Publications

Published under Bit Bros LLC

2026

The Decision Factory

A novel about decisions under uncertainty, with a foreword by Warren B. Powell, Professor Emeritus, Princeton University.

Best Seller — Stochastic Optimization View on Amazon

2025

The MILP Optimization Handbook

Introductory resource on linear and integer programming for applied practitioners.

Best Seller — MILP Optimization View on Amazon

2025

The Linearization Handbook for MILP Optimization

Practitioner's guide to modeling tricks and patterns for linear and integer programming.

Best Seller — MILP Optimization View on Amazon

2024

You Got the Data Job... Now What?

Practical strategies and frameworks for advancing in data and decision science careers.

Career Development View on Amazon

Research

Oakland University — w/ Dr. Serge Kruk

On the Automated Discovery of Facet Inducing Inequalities

Combinatorial optimization · Convex hull · Fourier-Motzkin algorithm · Constraint programming

White Papers

Gurobi Optimization

Intelligence, Optimization, and the New Decision Frontier (2026)

Patents

Ford Motor Company

Dynamic programming-based route optimization algorithm — US20210133643A1

Notable Endorsement

Featured by Warren B. Powell, Professor Emeritus of Operations Research at Princeton University, as a collaborator in supply chain optimization at Toyota. Powell wrote the foreword for The Decision Factory and references the book on his CASTLE Lab research page .

Princeton CASTLE Lab — Framing the Problem

Speaking & Media

Host Gurobi Optimization

From Classroom to Career: Building the Next Generation of Optimization Professionals

Webinar Panel Host — w/ Dr. Jeff Camm (Wake Forest), Dr. Ben Martin (Hanesbrands), Dr. Thiago Serra (U of Iowa)

Host LinkedIn Live

Recurring Live Events — Optimization, Decision Science & Careers

Solo & co-hosted w/ John Elam and others

Panelist DecisionCAMP 2026

Decision Intelligence Technologies — Annual Conference

Upcoming — August 26–28, 2026 · Online w/ Declarative AI 2026

Lecturer University of Edinburgh

Guest Lecturer — Decision Science & Optimization

Edinburgh, Scotland

Instructor Caltech × Simplilearn

AI/ML Bootcamp Instructor

Caltech Partnership Program

Podcast LokadTV

Explaining Optimization to Executives — Ep 184

w/ Joannes Vermorel & John Elam · Paris, France

Podcast Decision Intelligence Lab

Decision Intelligence & Applied Data Science

w/ Michael Watson

Podcast Data to Production

Bringing Data Science to Production

Episode 1 · Episode 2

Podcast DATAcated

Data Science & Analytics

w/ Kate Strachnyi

Podcast Data Career Jumpstart

Career Advice for Data Professionals

w/ Avery Smith, Founder

Technical Skills

Optimization & Simulation

GurobiCPLEXPyomoOR-Tools AMPLSimPyLPMILP MINLPQP / SOCPStochastic Optimization Robust OptimizationMulti-Objective Optimization Benders DecompositionDantzig-Wolfe Column GenerationLagrangian Relaxation Branch-and-BoundBranch-and-Price Cutting PlanesConstraint Programming Network OptimizationSensitivity Analysis HeuristicsMetaheuristics Genetic AlgorithmsSimulated AnnealingTabu Search Discrete Event SimulationMonte Carlo Simulation Agent-Based Modeling

Supply Chain & Decision Science

Vehicle Routing (VRP)Production Planning SchedulingDemand Forecasting Inventory OptimizationSupply-Demand Matching Facility LocationBin Packing Assignment ProblemsSequencing Decision IntelligencePrescriptive Analytics What-If / Scenario AnalysisDigital Twins

Programming Languages

PythonJavaSQLC++ RMATLABJuliaBash

Data Science & ML

NumPySciPyPandas scikit-learnTensorFlowPyTorch XGBoostLightGBMCatBoost ClusteringClassificationRegression Time Series ForecastingAnomaly Detection NLP (spaCy, NLTK)Reinforcement Learning Bayesian MethodsFeature Engineering Hyperparameter Tuning

Data Engineering & MLOps

DatabricksAzure MLAWS SageMaker SparkKafkaAirflow DockerKubernetesGitCI/CD SnowflakePostgreSQLMongoDB REST APIsTerraformdbt

Frameworks & Visualization

FlaskFastAPIDashStreamlit Spring BootHibernatePlotly MatplotlibSeabornPowerBI TableauJupyter

About Me

Optimization

Published Author

Co-Founder

LeetCode Lead

Patent Holder

Production Systems

Experience

Technical Account Manager

Co-Founder, Author & Tech Strategist

LeetCode

Data Content Lead

Solution Author

Toyota North America

Data Science Lead, Digital Innovations

Principal Decision Scientist II

Senior AI Consultant

Ford Motor Company

Data Scientist

Operations Research / Data Scientist

AI/ML Bootcamp Instructor

Software Engineer & Data Analyst

Mathematics Lecturer

Books & Publications

The Decision Factory

The MILP Optimization Handbook

The Linearization Handbook for MILP Optimization

You Got the Data Job... Now What?

Research

White Papers

Patents

Notable Endorsement

Speaking & Media

Technical Skills

Optimization & Simulation

Supply Chain & Decision Science

Programming Languages

Data Science & ML

Data Engineering & MLOps

Frameworks & Visualization

Honors & Awards

Growth Award

Recognition Award ×3

HackWSU — 3rd Place

Froemke Scholarship

Magna Cum Laude

Dean's List — Every Semester

VP — Mathematical Association

D1 Track & Field — Thrower

Education & Certifications

M.Sc. Industrial Applied Mathematics

B.Sc. Mathematics

Certifications View all on Credly

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