Cassie Kozyrkov

Kozyr

Speaking and advisory services. Request form: makecassietalk.com

Kozyr was renamed from Data Scientific.

Chief Executive Officer

Federal Reserve Bank of New York

Served a full two year term as Innovation Advisor and Councillor at the Federal Reserve Bank of New York, with a focus on the impact of AI on the financial markets and global policy.

Innovation Advisory Council Member

Google

Decision Intelligence is an interdisciplinary field concerned with all aspects of decision-making.  It combines Data Science (statistics, machine learning, AI, analytics) with the Behavioral Sciences (psychology, neuroscience, economics, and the managerial sciences).

I serve as a thought leader in this new discipline, guiding Google and the world in making safe, effective use of AI and data.

Chief Decision Scientist

My mission is to democratize artificial intelligence and guide business leaders in harnessing the transformative power of machine learning.

Chief Data Scientist, Office of the CTO

Youngest ever member of Google's Office of the CTO, specializing in AI and data science.

I'm also a coauthor of Google's Technical Director training program to teach others how to succeed in the role.

Technical Director, AI and Data

My roles are: statistician, machine learning expert, mentor, data scientist, evangelist, decision scientist, and consultant.  I bridge the gap between leaders and quantitative analysts / researchers.

As Google's statistics and machine learning sensei:
* I've advised 200+ teams at Google on their analytics processes.
* My ideas have sparked 400+ new projects.
* I've trained 20,000+ analysts/leaders/engineers in rigorous data-driven decision-making and/or using machine learning to transform their work.

Largest projects in: Search Advertising, Google Maps, Machine Intelligence, Infrastructure, YouTube

Statistician

Self-Employed

Data science consulting and analytics services for clients from government organizations, private sector firms, and academia.

Data Science Consultant

North Carolina State University

Statistics Lecturer

Statistical Computing, Advanced Topics in Statistics: Big Data, Special Topics in Statistics: Data Mining, Applied Time Series Analysis, Applied Multivariate Data Analysis, Advanced Probability and Measure Theory, SAMSI Computational Advertising, Statistical Methods II, Statistical Consulting, Statistical Theory I, Statistical Theory II, Linear Models and Variance Components, Stochastic Processes, Doctoral Research, Supervised Doctoral Teaching, R Programming

Mathematical Statistics PhD Student

Duke University

Psychology & neuroscience with specialization in transcranial magnetic stimulation (TMS) methods and the science of decision-making.

Neuroeconomics PhD Candidate

Center for Cognitive and Social Neuroscience at the University of Chicago

Coordinated lab research projects and team effort. Designed and ran experiments.

Project Manager

Charitable contributions and decision-making research with Professors Steve Levitt and John List.

Research Assistant - Prof. John List

Cassie is Google’s former Chief Decision Scientist and a sought-after AI advisor, working with senior leaders at places like Lenovo, NASA, and Gucci. She is currently CEO of Data Scientific and is known for founding the field of Decision Intelligence.

Cassie is a beloved personality in the data and AI community, followed by over half a million tech professionals. She is also a renowned keynote speaker and writer. ( If you'd like her to speak at your event, here's her booking form: makecassietalk.com )

In almost 10 years at Google, Cassie personally trained over 20,000 Googlers in data-driven decision-making and AI and has helped over 500 projects implement decision intelligence best practices. Before that, she served in Google's Office of the CTO as Chief Data Scientist. The rest of her 20 years of experience was split between data science, consulting, lecturing, and academia.

If you've had a good chuckle while learning about AI, statistics, or decision-making, chances are you've encountered her writing, which has reached millions of readers. She has been honored as a LinkedIn Top Voice for 5 years and as a #1 Artificial Intelligence writer on Medium for 7 years.

Speaking and advisory services. Request form: makecassietalk.com

86% of enterprises plan to invest more in agentic AI.
6% trust agents to run core processes.

Let's talk about that gap!

Harvard Business Review just released some findings about tech decision-makers (n=603):
🤖 86% expect agentic AI investment to grow in 2 years
🤖 6% fully trust agents with end-to-end processes
🤖 ~25% say they're "ready" on infrastructure, data, security, and governance

That lack of trust is a good thing, in my opinion. Trusting complex probabilitistic systems without re-archtiecting complex processes is a recipe for kablooies. If anything it should give you hope. The trouble is that the redesign is difficult except in narrow use cases.

The model isn't the bottleneck anymore.
The plumbing and the people are.

Fragmented apps and data → agents can't get reliable context 
Legacy processes → never designed for autonomous execution 
Security and compliance → no playbook for "agents at the core" 
Employees → unclear if agents are tools or replacements

The report points to enterprise orchestration as the missing layer—connecting systems, standardizing actions, enforcing governance so agents behave predictably instead of becoming shadow IT.

Old question: "Which LLM should we use?"
New questions:
Which processes are we willing to redesign around agents?
How do we orchestrate data, tools, and guardrails so we can trust them with real work?

In 3 years, the gap won't be "who has agents."
It'll be who rebuilt their processes so agents can actually run them.

Where is your team right now?
A) Still experimenting at the edges (help desks, copilots) 
B) Re-architecting workflows so agents own real outcomes 
C) Somewhere in between, trying to figure out where to start
D) Waiting and watching others stub their toes

Drop your letter below. Your comments make my (digital) world 'round.

P.S. On a completely different note,  my Decision-Making with ChatGPT course is running on demand right now with a live Q&A with me next week. Come ask me anything! decisiongptcourse.com

CEO, Google's first Chief Decision Scientist, AI Adviser, Decision Strategist, Keynote Speaker (makecassietalk.com), LinkedIn Top Voice

Agentic HBR

Been wondering when my next cohort will be? Surprise! The time is NOW. If you missed the previous run or have been waiting to join, enrollment is now live:

 👉 https://lnkd.in/eG7EBtTv

The last cohorts made something clear: leaders aren’t looking for more information. They’re looking for clearer judgment. ChatGPT helps - but only when you use it in the right parts of the thinking process.

In this cohort, we’ll continue the work of turning AI into a genuine thinking partner instead of a shortcut. You’ll learn how to:

• Use ChatGPT to reduce effort without losing rigor
• Avoid the trap that turns “AI-assisted” into lazy thinking
 • Spot cognitive biases before they distort outcomes
 • Separate luck from decision quality
 • Build a decision scribe so you finally learn from your choices
 • Operate with confident judgment instead of drowning in advice

You’ll get 30+ on-demand videos (available as soon as you enroll), a 2-hour live Q&A with me (at 1 PM ET Dec 18), prerecorded Q&A from earlier cohorts, templates, frameworks, and a global community.

If you're working on sharpening your thinking in an AI world, Cohort 3 is now open.
 👉 https://lnkd.in/e-RaxVJJ

If this resonates, a repost or subscribing to decision.substack.com helps the course reach the leaders who need it.

#DecisionIntelligence #AILeadership #StrategicThinking #DecisionMaking #AI

Priceline

Reporting to the Vice President of Business Analytics, Curtis leads a highly engaged team of data scientists and machine learning engineers focused on delivering scalable machine learning-based solutions to drive significant business growth and value. Under Curtis' leadership, the team is responsible for shaping the product vision, strategic roadmap, and implementation of analytical frameworks for key Data Science initiatives. These include refining dynamic pricing strategies, advancing operational analytics with anomaly detection and performance metric forecasting, and crafting user-facing predictive tools to boost user experience and revenue.

Senior Manager, Data Science

On the Personal & Commercial Banking Performance Management team, Curtis was responsible for developing and deploying scalable econometric models that supported Enterprise Stress Testing. Curtis had a direct impact on strategic business decisions with Enterprise Stress Testing being a primary decision-making tool used by senior management and the Board.

Senior Manager, Financial Modeling & Analytics

On the Investor & Treasury Services Business Intelligence team, Curtis was responsible for developing and supporting data driven solutions from concept to production. Curtis also supported Executive decision-making by identifying key insights through statistical analysis and data visualizations techniques.

► Leveraged unsupervised machine learning techniques (k-means, DBSCAN) during EDA initiatives
► Developed regression and NLP-based classification models using Python (pandas, NLTK, scikit-learn, XGBoost)
► Created high-impact presentations and dashboards for stakeholders using Power BI and Tableau

Manager, Business Intelligence

On the Financial Reporting & Tax team, Curtis prepared financial statement packages for investment fund clients including Sun Life Financial, Manulife, CI Investments, and Educators Financial Group. Curtis also liaised with internal and external auditors to ensure compliance with International Financial Reporting Standards (IFRS).

► Developed business process automation scripts with Python, R, and VBA frameworks
► Efficiently orchestrated multiple concurrent projects across cross-functional teams
► Guided and developed a team of data analysts in leveraging Python and R for process automation

Senior Analyst, Financial Reporting & Tax

On the Financial Reporting & Tax team, Curtis supported the preparation of financial statement packages for investment fund clients. Curtis also saved over 2000 FTE hours on an annualized basis by developing a variety of business process automation scripts with Python, R, and VBA frameworks.

► Conducted comprehensive research and analysis on the accounting and tax implications of corporate actions, including complex ones, for Funds, leading to recommended tax treatments

Analyst, Financial Reporting & Tax

CAA Club Group of companies

On the Corporate Sales team, Curtis adeptly negotiated client contracts and handled sales inquiries. He led efforts to simplify and automate internal processes, boosting department efficiency. Curtis also built strong collaborations with Agency Sales, Marketing, and external partners, driving the seamless execution of marketing materials, tradeshow setups, corporate events, and the production and distribution of a quarterly newsletter.

Associate, Corporate Sales

On the Retail Banking team, Curtis efficiently processed financial transactions for clients, such as deposits, 
withdrawals, bill payments, and wire transfers. He also actively engaged with clients to understand their immediate and future financial goals, ensuring their needs were met with personalized solutions.

Customer Service Representative, Retail Banking

🏝️ Data Science Manager @ Priceline

Data-driven leader, passionate about uncovering insights through analytics and their implications for strategic decision-making. Focused on driving growth and innovation through the power of data. Strategic thinker, problem solver, and innovator. Skilled in translating complex data into actionable strategies that drive business success, enhance customer understanding, and foster product development. Relationship builder, team leader, and mentor. Excited by the challenge of big data and the meticulous details that underpin predictive analytics and tangible ROI.

Experience in: Data Analytics, Predictive Modeling, Business Intelligence, Strategic Planning, Data Visualization, Big Data Technologies, Machine Learning, Customer Analytics, Product Development, Data Governance, Team Leadership, Mentoring, Cross-functional Collaboration, Stakeholder Engagement, Innovation Management, Process Improvement, Decision Support Systems, and ROI Optimization.

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Cassie Kozyrkov

Curtis Raymond, MMA

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The Battle

Cassie Kozyrkov

Curtis Raymond, MMA

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Cassie Kozyrkov's LinkedIn Performance

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