Machine Learning @ Call of Duty | Rebel Data Scientist | Click follow to join a community of data, gaming, and tech professionals 🎮

Databricks

As a Field CTO in the Databricks gaming vertical, I am an external technical strategist helping game studios unlock the full potential of their data. 

As a hands-on solutions architect, I design and implement scalable, future-ready systems that empower developers to build next-generation player experiences, run efficient operations, and turn innovation into impact.

My role blends technical strategy, architectural design, and industry evangelism. I work directly with game studio leadership to architect the infrastructure that enables smarter game design and better live operations.

Ultimately, I help studios create leverage with their data so they can focus on what matters most: building great games that players love.

Field CTO, Gaming

ggAI

We are the next generation of future-ready game data geeks - engineers, analysts, ML practitioners, and technical leaders - united by a belief that collaboration and openness are the keys to unlocking better player experiences. 

Whether you're scaling infrastructure, tuning personalization models, or wrangling event data, GGAI is where the gaming industry's sharpest minds come together to share best practices, solve hard problems, and build what’s next.

Founder

Rebel Data Science

Rebel Data Science brings a refreshingly authentic approach to educating both people and brands working on AI. By making data science and AI more accessible, we hope to open up doors for women to find fulfilling careers in data. We are excited about partnering with brands who share our commitment to our communities.

Microsoft

Director, Engineering

Activision

As a Director for Call of Duty, I led a team focused on game security. 

We utilized a suite of technology to make decisions in real-time and strengthened the technology that delivers low-latency concurrent experiences to hundreds of millions of players.

Senior Manager, Machine Learning Engineering

As an expert machine learning engineer, I implement and oversee machine learning projects to detect and minimize disruptive behavior in online gaming.

Staff Machine Learning Engineer

As a Senior Data Scientist on Call of Duty’s behavioral machine learning team, I worked at the intersection of big data engineering, real-time data analytics, and behavioral modeling to drive business value in both paid and F2P online games. 

I balanced hands-on model development while collaborating cross-functionally with my stakeholders across Activision.

•	Managed a team of data scientists developing distributed machine learning models to support behavioral machine learning initiatives
•	Built, refined, and executed a roadmap for a behavioral machine learning approach to anti-disruptive behavior
•	Outlined team best-practices including library packaging, versioning, containerization, CI/CD and task-scheduling
•	Triaged and shaped incoming requests and supervise team deliverables

Senior Data Scientist

Game Security Group (GSG)

The Game Security Group (GSG), is the video game industry's preeminent information-sharing and analysis center that servers as a central resource for exchanging information on cyber threats. The GSG is comprised of 23 companies and facilitates in-person and virtual meetings for members to discuss security challenges and approaches to defending their corporate and game infrastructure.

Governing Council Member

Well Data Labs, Inc

As a Data Scientist on the Well Data Labs Research and Development team, I focused on how data science and machine learning can impact operational efficiencies in the oilfield and increase the ROI of unconventional wells. 

•	Developed, deployed and patented static and real-time machine learning models to automate the recognition of events in time-series metered data
•	Conducted customer discovery and authored studies that addressed key market needs while proposing solutions and strategies to business challenges
•	Prepared and delivered internal and external industry presentations to effectively demonstrate the value of data science in oil and gas
•	Worked collaboratively in an agile environment with Product and Engineering teams on prototyping, designing and implementing robust production-ready business solutions
•	Created documentation and project artifacts for maintaining production code for machine learning platform
•	Explored and visualized data to find actionable insights and developed robust pipelines to automate reporting for Professional Services

Data Scientist - R&D

Associate Data Scientist

AirDNA

As a Product Analyst at AirDNA, I leveraged, visualized and transformed short-term rental data into strategic, actionable analytics to inform decisions resulting in 120% YOY growth and a projected $6.8 million run rate.
 
•	Acted as the point-person on all things related to user data and analytics, from data ingestion, maintenance and tracking, to understanding and reporting
•	Prepared and delivered executive presentations to strategically meet growth objectives
•	Explored and visualized data to find actionable insights and make product recommendations through funnels, churn risk analyses, cohort analyses, customer lifetime value, and behavioral segments
•	Utilized a comprehensive understanding of the full-stack framework to implement and integrate front-end and back-end analytics solutions 
•	 Created documentation and project artifacts such as analytics schema, user stories, process diagrams, work-flows, and technical requirements
•	Prepared specialized market analyses for content creation in high-level publications such as the New York Times and Wall Street Journal

Product Analyst

Analytic Partners

As a Marketing Analytics Consultant at Analytic Partners, I built predictive models to improve marketing ROI and executed communication strategies across five divisions at two Fortune 100 companies. 

•	Developed predictive attribution and media mixed models
•	Outlined the impact of advertising for five individual divisions across two Fortune 100 companies
•	Addressed client specific business challenges while executing communication strategies and presentations to convey actionable insights
•	Extracted and synthesized information from multiple data sources while proactively performing data validation to ensure accuracy, quality and integrity of data
•	Work collaboratively as a consultant with colleagues in sales, marketing, and finance to provide data-driven recommendations for client resource allocation

Marketing Analyst

University of Colorado

As a Computational Researcher, I worked at the intersection of theoretical physics, chemistry, and computational modeling to simulate the behavior of electrons in photochemical reactions.

•	Utilized quantum simulation packages on massively parallel super-computing systems to model the behavior of electrons in photochemical reactions
•	Explored systems which had previously been limited to a mixed QM/MM approach
•	Author of 3 published articles, one of which was in a Top 10 journal
•	Earned grant worth over 1 million computational hours on the 8th largest supercomputer in the world
•	Worked with large, complex data sets generated by massively parallel super-computing systems
•	Spearheaded successful and ongoing summer internship program for at-risk high school students focusing on computer science, chemistry and biotechnology

Computational Chemist

- All views shared are my own opinion and do not reflect the stance of my employer

🎰 Vegas born
🧪 Ex-chemist, current data scientist, lifelong gamer. 
👩‍🔬 Advocate for women in STEM, tech, and gaming.
🚨 Security strategist at Activision. 

Have you ever wondered “what comes after breaking into data science?” I share tips on how to excel in your career - advocate for yourself to get promoted, navigate situations with leadership, and mindfully leverage your strengths to optimize your career. 

Carly is a data scientist, computational chemist and machine learning engineer. She obtained her M.S. in chemistry from the University of Colorado focusing on computational quantum dynamics. She has authored multiple peer-reviewed publications and holds two non-provisional machine learning patents. 

When she isn't writing about herself in the third person, building mechanical keyboards or neglecting the oxford comma, she works as a public speaker, author and content creator focusing on AI. 

More specifically, she applies Python-based machine learning and best practices in statistical analysis to creatively solve novel problems. This includes harnessing various toolkits to model real-world structured and unstructured data and drive business value to stakeholders at all levels of the organization. 

Areas of Expertise: data science, machine learning, fraud detection, trust & safety, distributed systems, leadership, team-building, time-series and dynamic modeling, anomaly detection, biotechnology, high-frequency signal processing

Languages:
- Python (NumPy, Pandas, PySpark)
- SQL
- Scala

ML Platforms:
- TensorFlow
- Keras
- Scikit-learn

Engineering:
- AWS
- GCP
- Docker
- Apache Spark
- Flask
- Airflow
- CI/CD (Jenkins, Kubernetes)

Carly Taylor, M.Sc.

- All views shared are my own opinion and do not reflect the stance of my employer

🎰 Vegas born
🧪 Ex-chemist, current data scientist, lifelong gamer. 
👩‍🔬 Advocate for women in STEM, tech, and gaming.
🚨 Security strategist at Activision. 

Have you ever wondered “what comes after breaking into data science?” I share tips on how to excel in your career - advocate for yourself to get promoted, navigate situations with leadership, and mindfully leverage your strengths to optimize your career. 

Carly is a data scientist, computational chemist and machine learning engineer. She obtained her M.S. in chemistry from the University of Colorado focusing on computational quantum dynamics. She has authored multiple peer-reviewed publications and holds two non-provisional machine learning patents. 

When she isn't writing about herself in the third person, building mechanical keyboards or neglecting the oxford comma, she works as a security strategist for Call of Duty at Activision Publishing. 

More specifically, she applies Python-based machine learning and best practices in statistical analysis to creatively solve novel problems. This includes harnessing various toolkits to model real-world structured and unstructured data and drive business value to stakeholders at all levels of the organization. 

Areas of Expertise: data science, machine learning, fraud detection, trust & safety, distributed systems, leadership, team-building, time-series and dynamic modeling, anomaly detection, biotechnology, high-frequency signal processing

Languages:
- Python (NumPy, Pandas, PySpark)
- SQL
- Scala

ML Platforms:
- TensorFlow
- Keras
- Scikit-learn

Engineering:
- AWS
- GCP
- Docker
- Apache Spark
- Flask
- Airflow
- CI/CD (Jenkins, Kubernetes)

CTO | Ask me about good data, great teams & better systems

When I was a junior data analyst,
I’d stare at my screen pretending to “debug”
 
...when in reality I had no idea what planet my code was on.
 
And in the middle of all that confusion,
there was one senior who changed everything for me.
 
- He didn’t sigh.
- He didn’t look annoyed.
- He didn’t give me that look that says,
 
“Why is this kid even here?”
 
He just pulled up a chair and said,
“Show me where you got stuck.”
 
Then he walked me through it.
 
Slowly. Patiently. Encouragingly.
Like my questions weren’t ridiculous.
 
At the end he said,
 
“You’ll get there. Everyone starts somewhere.”
 
I didn’t realize how much I needed
to hear that until he said it.
 
Because the part most people don’t admit is:
 
A lot of folks in tech will watch you struggle in silence.
 
But every once in a while, you meet
someone who doesn’t play that game.
 
+ Someone who teaches without ego.
+ Someone who explains without condescension.
+ Someone who sees your effort before your mistakes.
 
If you’re lucky enough to meet
that person, your whole career shifts.
 
Mine did.
 
That support carried me forward:
Data analyst → manager → head of IT → CTO
 
And now I try to be that person for others.
Not because I’m trying to be inspirational.
 
Just because someone did it for me...when
I honestly was one bad week away from quitting.
 
Careers don’t get built alone.
 
They get built by the people who notice
you right when you needed to be noticed.
 
So here’s the real question:
 
Are you ready to be that person for someone else?
 
P.s: To that senior, I still owe you 4,932 coffees.
 
P.s.s: Mention that senior of yours and thank them.

Engineering | Gaming 🎮 | AI

If you want to read a happy Thanksgiving post, just scroll right on by this one…

Things are not okay right now for a lot of people. 

I’m sure you’ve noticed too - viral posts about fellow professionals who are about to lose everything. They’ve been laid off, unable to find work, and some are about to be homeless. 

I don’t want this to become the new normal. 

Being so lost and hopeless that you are begging for work on LinkedIn is, in fact, not normal. 

And it flies in the face of everything you’re told about people who struggle.

“Oh they don’t have the right degree.” 

“They must be addicts.” 

Nope. Just regular people like you and me. 

The astounding wealth transfer in the U.S. driven by layoffs, AI, and tied up with a pretty little bow we call “shareholder value” is not normal. 

There is an armed guard at my local grocery store checking receipts because of theft. And instead of addressing issues like inflation and price gouging by the grocery store, we accept this as normal. 

We accept that the cashier who checked us out is on food stamps. 

Corporate greed at this magnitude is not normal. 

I have a lot to be thankful for. I could spout some happy platitudes as I sit here in the airport writing this note. 

But that’s not why I’m here. And I don’t think it’s why you’re here either. 

I am using my platform to say none of this is normal or okay.

And I’m tired of it.

My thoughts on the AI bubble…

AI is not profitable yet. 

Big companies, like Oracle, and small companies, like Lambda, are borrowing money to fund their AI ventures. 

If AI becomes profitable, a lot of this debt will be paid back. But even if AI becomes profitable, some companies will fail, and some will succeed. This is normal. 

However, if AI fails to become profitable, asset backed securities (sound familiar? Think 2008 housing crisis) that are propping up some of these AI companies also fail. As companies default on their loans, these ABS will become devalued and can trigger other defaults. 

About $13.3B in ABS have been created and issued as companies race to build data centers. 

How widespread the effects of default could be depends on how this debt is being traded and who is holding the bag if things go south. 

Making AI profitable should be a key concern for everyone involved. But as we rob Peter (massive layoffs) to pay Paul (fund AI), the idea that consumers will consume enough for AI to be profitable seems pretty far fetched. 

I do believe there is a path forward for AI to become profitable, but too many AI strategies are to layoff employees to fund simple (and, quite frankly, unimaginative) chatbot projects which are NEVER going to move the needle towards profitability. 

Profitability requires novelty and innovation.

“We should just hire the best person for the role regardless of gender.” 

This is what I hear every time I talk about the dropoff of women at higher levels in an organization. 

The issue with this mentality is that it assumes you are interviewing a proper distribution of people that you can assume “the best” person is in your interview funnel. 

But the reality (most of the time) is that the folks being interviewed or considered for promotion are NOT a representative sample and therefore “the best” person is probably not even in consideration. 

So instead of hiring “the best” person for the role, you hire “the best” person that you’re aware of. 

And you don’t even realize your awareness of “the best” is limited because it’s hard to know what you don’t know. 

But this is exactly why we talk about it. 

Having a 60% decrease in women at the entry level vs director level in an organization is not just because “the best” candidates for director+ are 90% men. 

I don’t know what exactly is happening (we’re losing women along the way to cholera and dysentery, probably) but it is worth discussing.

Let’s all shake hands and agree we’re not going to break things anymore 

Crowdstrike 🤝
AWS 🤝
Cloudflare 🤭

I have the best job 🤩

Thanks for hosting us Mojang Studios!

I can’t believe it’s already been over a month since #BigDataLDN! 

UK friends - thanks for the hospitality!

It still amazes me that Big Data LDN is totally free to attend. I think other large conferences could learn a thing or two about how to put on a free conference that actually provides value!  

P.S. I’m always available for speaking opportunities. DM me! 😇

to all the women in my network who “ruined the workplace” today… 🫶😍

On this weeks episode of “where in the world is Carly?” she can be found 

- eating Peking duck with the one and only Melissa 
- doing awesome anime things with the talented crew at Crunchyroll 
- hopping on a late night flight and catching the northern lights from the window  

Next up is Vegas!

Update from AWS re:invent in Las Vegas this week…

AWS just announced 60 AI Competency Partners and Databricks is one! 

I see so many names of great companies I’ve worked with that support Agentic AI Applications, Agentic AI Tools, and Agentic AI Consulting Services.

This is super exciting and a huge honor! Strong partnerships like this mean strong innovation for all customers across AWS  💪

We love to see it! 

Check our updates to marketplace here! https://lnkd.in/gSd9ymET

Brand partnership • Engineering | Gaming 🎮 | AI

SEGA... i love being a floating head in your meetings, let's do it more often 🥹  

Thanks Felix Baker and Stuart Wright for having me for an industry Q&A session today. Always a pleasure talking shop with the awesome teams at SEGA Europe!!!

I don’t usually like to shill but this is actually really cool…

If there’s one thing Databricks excels at it’s making the hottest tech that all of the cool startups are playing fast and loose with available safely at enterprise scale. 

I’ve seen so many folks duct taping together solutions for MCP servers without consideration for governance or security. 

So we decided to build an MCP Catalog right into Databricks to serve as a one-stop shop to discover, connect to, and govern all the MCP servers in your organization. 

And the MCP Marketplace provides secure access to a growing ecosystem of external tools and data from trusted partners, empowering developers to easily build high-quality, governed AI agents.

Neat! 

What partners would you like to see in the Marketplace?

Yo Crunchyroll … why’d you never tell me you were so legit 🫶😸

are we in an 🤖🫧? 

asking for a friend

Drew Maring and I are vibe coding the next big thing in aviation safety 👀 

And we’re coming out of stealth mode this Sunday! 

Hold onto your butts.

taplio

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taplio

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