Global Data Office - Head of EY.ai Simulation Labs

Spearhead strategic development and market positioning of Tax AI - driving its adoption and success through innovation, education, and community.

Global Tax AI Labs - Strategy Lead, Simulations & Synthetic Data

CDP provides a platform where professionals can develop technical skills, ideate on ways to improve internal and client work processes, and build re-usable tools for anyone in the firm.

From cultivating an innovative mindset within the community to leading product development and market reach, the vision is to share the tools to automate repetitive work and have professionals focus on more purposeful, needle moving work.

Americas Innovation - Crowdsourcing Development Platform (CDP) Product Manager

Research and build innovative, robust, and flexible financial analysis and modeling solutions to provide insight into client decisions for strategic planning, investment valuation, financial forecasting, and M&A transactions.

Decision, Modeling & Analytics Senior Manager

The Real Estate Tax technical liaison with the Tax Technology and Transformation team on the development of the "next-generation" technology for the partnership/fund tax compliance process.

Led the way for the automation and redesign of numerous tax workpapers and processes for partnerships and corporations for multiple engagement teams.

Selected as the Senior Manager Sponsor for EY's counseling family -- providing emotional and work support, facilitating coaching and career development discussions, and organizing events for team bonding.

Real Estate Tax Senior Manager

Oversaw tax compliance and advisory engagements for both domestic and international real estate firms. 

Experience with federal, state and international tax issues, including year-end K-1 reporting, quarterly estimates/withholding, REIT compliance, REIT due diligence, and transactional planning in complex partnership structures.

Real Estate Tax Manager

Deloitte

Advised Fortune 500 companies worldwide regarding tax opportunities on inbound and outbound operations. 

Designed, collaborated, and reviewed various tailored tax models using large data sets to quantify and measure the impact of tax planning strategies on clients' tax profile. Modeling support ranged from complex tax attribute projects to M&A and global restructuring transactions.

International Tax - Quantitative Consulting Services Manager

Managed the development of the Integrated International Tax Reform Model to help companies quantify the potential impact of various tax reform provisions and its interplay, including transition tax, global intangible low-taxed income, foreign derived intangible income, base erosion and anti-abuse tax, and interest expense limitation. 

Developed a Global Funds Model focused on global real estate and infrastructure funds to help assess fund structuring alternatives, tax reform planning considerations (e.g., impact of 163(j), 100% expensing), and other tax structuring considerations (e.g., internal leverage, withholding leakage, exit considerations, etc.)

International Tax - Quantitative Consulting Services Senior

Manage and led staff on year end compliance process, which involves review of tax basis balance sheets and capital accounts, partner allocations in accordance with 704(b) regulations, review of partnership agreements for allocations, and Schedule K-1 reporting.

Selected by Directors and Partners to participate in various committees: (1) Quality and Risk Management Committee, (2) Campus Recruiting, (3) Google Guide and (4) Market Tax Technology Team.

Real Estate Senior Associate

Prepared and reviewed federal, international, state and local, partnership and corporate tax returns for clients in the Real Estate industry. She took the initiative to streamline repetitive, manual processes via automation using technologies such as Visual Basic and JavaScript.

Real Estate Tax Associate

Ernst & Young

National Tax Technology Group

Real Estate Tax Intern

Goldman Sachs

Federal Tax Intern

Empire State Development

Accounts Payable Intern

Macy's

Human Resource Staffing Intern

I Help Corporate Professionals Gain Career Clarity & Fulfillment | Founder @Amplify Your Home | Global AI Tax Copilot Strategist @EY

Don't be fooled by my appearance. Quiet, Asian, tiny girl.

In the last decade, I've...

Successfully navigated the corporate giants: Goldman Sachs, PwC, Deloitte and EY.

Built communities, tax and financial models, and automations. (Excel wizard here)

Empowered employees to own their damn careers,

Challenge their norms to do something special.

That's when Problems become Opportunities,

Strategies into Actions.

You are not Alone.

Ready to redefine your career? Let's make it happen.

Mary Fung

Everyone’s racing to adopt AI.
No one’s stopping to ask what it’s supposed to mean.

The irony?
AI won’t save broken systems. It’ll just expose them faster.

The question isn’t “How fast can we adopt AI?”
It’s “What problem is worth automating in the first place?”

Own Your Damn Career | Founder @Amplify Your Home | Head of Synthetic Data & Simulations @EY

Here’s what employees actually hear when you say “AI transformation”:

“Do more with less” → Your role is shrinking.
“Automate the boring work” → We never valued that work to begin with.
“Upskill” → Figure it out yourself or you’re gone.

You might mean innovation.
They hear elimination.

That’s the real disconnect slowing enterprise AI rollouts.

Not the tools.
Not the tech.
Not the budget.

It’s fear. It’s mistrust.

It’s silence in meetings where everyone nods but no one says what they’re really thinking:

“Will I still matter when this goes live?”

I keep banging the drum on this one.
Business folks are just as - if not more - important than data scientists in AI.

Because it doesn’t matter how good your model is
if no one in the room actually knows what “good” looks like.

Most orgs don’t have an AI problem.
They have a domain judgment problem.

The people who actually know their craft - the ones who can look at a model’s output and say “that’s wrong” without a dashboard -
are the ones who’ll make AI useful.

You don’t need more data scientists.
You need more people who know what they’re doing.

AI isn’t taking people’s jobs. It’s deleting the entry point.

A Harvard study found that when companies start using AI, they don’t usually fire people -
they just stop hiring beginners.

So the seniors stay.
But no one new comes in.

That might sound smart in the short term,
but it’s a slow disaster - because those “junior” roles were how people learned the craft.

If no one learns the basics,
who becomes the next expert?

AI didn’t remove opportunity.
It removed training disguised as busywork.

Now companies have to build real ways for people to learn...
or they’ll run out of people who actually know what they’re doing.

This is the shift no one wants to admit:

Automation isn’t killing careers.
It’s killing bureaucracy.

The people who’ll thrive aren’t the ones defending old roles.

They are the ones rebuilding new ones around intelligence, not repetition.

The question isn’t “Will AI replace us?”

It’s “Are we doing work that deserves to survive?”

Every company has both:

People who follow processes.
And people who question, rework, rebuild.

Before AI, that difference was subtle.
Now it's blindingly obvious.

Because AI gives leverage.
But only to those who know how to use it.

So the gap grows.

The followers wait for instructions.
The builders get 10x output, quietly and consistently.

This isn't about who's smarter.
It's about who's playing offense with new tools.

Ask better questions.
Builder sharper scaffolding.
And use AI to do your thinking, not replace it.


https://lnkd.in/eb-ycK-e

Woohoo, I made it in the hype video

Life goal accomplished!

It's almost time for #MSIgnite!  Will you be joining us on the show floor or in the #EYFrontierZone where you can dive into proven AI strategies, learn more about the #TaxDepartmentoftheFuture, and hear from #EY and #Microsoft leaders?  Learn more here https://lnkd.in/eRKECYDq 
#EYMicrosoft #AgenticEnterprise #AgenticFrontier #Tax
Colleen Sebra Christopher Aiken Daren Campbell Justin Shafer Ivan Roussev Suzi Russell-Gilford Coskun Cavusoglu Jon Cisler Phillip Mazzie Kristen Matthews, MBA Rory Moore Rebecca Paterson Jessica Maher Dhivya K

If your job is just tasks, you’re not an employee.
You’re a cog.

That’s what Jensen meant when he said:
“Your job has to be more than the task.”

Because the task is the part AI eats first.
The checklist.
The template.
The handoff.
The thing anyone could do with enough time and instructions.

If that’s your identity at work, you won’t survive this wave -
not because you're not smart,
but because the system never asked you to be anything more.

AI exposes that.

It shows you exactly where you’ve been replaceable all along.

The future belongs to the people who stop being the task and start being the reason the task exists.

Everyone’s sharing AI “tips.”
No one’s sharing AI use cases that actually make money.

Because the people who’ve found them don’t have an incentive to share.
If AI can replace 80% of your job, why would you publish the proof?

So what we get instead are demo reels and productivity hacks - not the deep workflows where AI is already transforming value creation.

The irony?
The AI revolution isn’t waiting for new models.
It’s hiding inside the quiet use cases no one will talk about.

AI isn’t being driven by people who need to justify budgets.
It’s being driven by people who think losing this race means irrelevance.

That’s why Big Tech keeps spending while others keep debating.
They’re not chasing profits. They’re chasing permanence.

If you’re still running an ROI analysis while the world rewires itself...
you are already late.

Self Employed

Entrepreneurship reset my approach.

I built, experimented, and focused on what drives results:

→ Strategy is everything in AI.
→ Real impact needs execution and leadership.
→ Teams drive value, not just ideas.

In the past year, I helped CEOs & founders. 
Together we turned AI into actual business value.

✅ Built AI systems that saved 100s of hours/month
✅ Helped leaders apply AI fast and with confidence
✅ Drove new product growth from zero to traction
✅ Launched lead gen engines delivering 5–10 qualified leads/week
✅ Driven ideation and growth of new AI products
✅ Coached founders to viral growth, product validation and more 

I also built a trusted voice in the space:

→ 9,000+ audience
→ 1.5M+ annual impressions
→ #1 AI/ML voice in Estonia (Favikon)

Today, I advise companies on:

Today, I help tech companies:

→ Define and execute AI adoption strategies
→ Align AI projects with business growth
→ Build internal AI teams and workflows

Looking ahead, I'm seeking a role where I can:

→ Lead AI product or transformation initiatives
→ Scale high-performing, driven teams
→ Drive business outcomes that matter

If you're building with AI, maybe I can help.
Let's talk about how to make it real!

AI Strategy & Growth Consultant

Zentrik

Zentrik had strong tech, but unclear messaging.

The story didn’t land. Growth had stalled.

I stepped in to lead positioning and GTM.
→ Refined messaging to target early adopters
→ Built trust with strategic AI-driven content
→ Set up a full growth engine from scratch

In just 4 months, we turned it around.

→ Doubled users through focused content & strategy
→ Hit 20K+ weekly impressions, higher visibility
→ Improved conversions and link to early adopters
→ Built a content system that kept new users flowing

Zentrik had the product.
I made sure the right people saw it.

Head of Product Growth

Philips

I led AI-driven feature work on a flagship CT system.

This was Philips' top-priority product in СT imaging.

→ Prioritized key features across tech and product
→ Delivered 80%+ of roadmap milestones on time
→ Aligned work across R&D, research, and clinical

I also continued to drive AI innovations
Integrating deep tech that mattered.

→ Integrated AI-based denoising
→ Increased image clarity and noise reduction
→ Validated results with clinical partners in the loop

To scale this work, I built lean systems.

→ Created frameworks for model testing and review
→ Automated dev flows to speed up iteration

We made AI practical and impactful for clinicians.

Product Owner

I earned my first official leadership role in 2021.

It started with doubt — and turned into trust and results.

I led an AI & imaging research team of 12–13 people.
We delivered real impact, year after year.

→ Drove 40+ patents and 10+ key innovations yearly
→ Built one of the top-performing teams in the lab
→ Maintained 90%+ engagement year over year

Leadership was more than output.
In fact, it was personal.
Mentorship and team growth always remained top priority.

→ Helped team members grow into leadership roles
→ Created non-intrusive systems for team support

I also led beyond my own group.
My role scaled with the org as it evolved.

→ Drove best practices across research leads
→ Supported Philips' global restructuring in 2023
→ Conducted 20+ interviews to grow the talent bench

This role taught me how to lead with clarity, care, and scale.

Imaging and AI Team Leader

Before leadership, I led with code and ideas.  

I pushed AI into imaging where it made impact.

→ Filed 12 patents tied to core imaging innovations  
→ Led 6 AI-driven initiatives across Predictive Analytics and CT  
→ Proposed 2 new projects — 1 secured exec support  

Beyond research, I built tools that helped others move faster.  

→ Built 3 frameworks for code, QMS, and workflows  
→ Sped-up AI experimentation and validation  
→ Improved team output with better dev practices  

I stayed hands-on throughout, pushing product-ready AI.  

→ Led model design for key imaging challenges  
→ Developed deep learning pipelines for denoising  
→ Shipped code used in clinical-facing prototypes  

This role built the foundation I still lean on today:
  
Ideas, execution, and systems that scale.

Senior Scientist

Ran a global release train for AI and imaging products.

50+ people, 5 countries, 1 mission: deliver at scale.

→ Managed cross-functional teams across 5 time zones
→ Oversaw a $5M+ innovation portfolio in medtech
→ Led delivery planning in a regulated SAFe setup

My role blended execution with strategic oversight.
We shipped high-value features, on time and on target.

→ Aligned stakeholders across tech and product orgs
→ Drove compliance with lean QMS processes
→ Coached Scrum Masters to boost team velocity

These projects weren’t just innovation on paper.
When shipped, they brought real business impact.

→ Key features drove tens of millions in revenue
→ Led to happy customers and patients

This role sharpened how I lead large, distributed teams.
High stakes. High complexity. Real results.

Release Train Engineer

I stepped up to coach two global Agile teams.
Early trust came from clear wins and steady delivery.

→ Led 2 teams across EU, India, and the US
→ Applied SAFe and Scrum to match our needs
→ Increased focus and alignment in day-to-day work

One team built models for predictive analytics.
We made them faster and more effective.

→ Delivered 10+ models used in real deployments
→ Hit targets across multiple project cycles
→ Saved $50K+ in the first year of rollout

I helped teams move faster with smarter systems.

→ Built 3 tools for workflows and compliance
→ Improved data handling and code quality
→ Streamlined dev work across research projects

This role shaped how I support teams at scale.
With clarity, structure, and trust — results followed.

Scrum Master

I started strong — filing patents within my first year.
I earned trust fast, and kept pushing for more.

→ Filed 6+ patents and research publications
→ Drove AI innovation in CT and X-ray systems
→ Secured public grants with in-house R&D matches

By 2018, I focused on predictive analytics at scale.
Cost savings, better models, and real-world use.

→ Built models to support X-ray service decisions
→ Achieved $50K+ in yearly operational savings
→ Shifted from MATLAB to Python + ML pipelines

In 2019, I co-led a €2M innovation assessment.
We spotted risks others missed and acted on it.

→ Uncovered misalignment in a major AI project
→ Redirected €1M to a stronger software initiative
→ That pivot later drove €100M+ in product revenue

I learned early how to turn insight into direction.
And how to speak up — when it mattered most.

Research Scientist

Stealth Startup

We set out to explore how AI could disrupt business.

The plan: test fast, grow lean, and stay hands-on.

With 3 other AI experts I co-founded my first start-up.
We focused on audience building and distribution.

→ Grew a newsletter to 1,000+ in 3 months
→ Attracted early sponsor interest

I led a 4-person team across ops and content.
We used AI to speed up writing and research.

→ Built systems for LinkedIn and newsletters
→ Created no-code workflows for trend tracking
→ Automated outreach and content ideas

This work sparked my own brand momentum.
That still continues to this day.

The startup paused as the team moved on.
But the systems & lessons still drive how I build.

Co-Founder

CEA - Commissariat à l'énergie atomique et aux énergies alternatives

PhD project in scatter correction in energy-resolved x-ray imaging

Doctoral Researcher

Tampere University Hospital

Master thesis project aiming at correcting metal artefacts in pelvic CT images

Master Thesis Student

North Estonia Medical Centre

A research project aimed at developing a software tool that would evaluate quality assurance indicator dependence on CT reconstruction parameters

Researcher

Statistical analysis of radiation dose across varying hospital machines and examination protocols

LBN Medical A/S

Technician

Roesys GmbH

Supercharging your content creation with AI | AI & Tech innovator | GPT Builder | AI Artist

I started driving AI innovation the hard way.

It was slow. Frustrating. Felt like pushing a boulder uphill.

I was juggling things like:

⚫ AI models stuck in endless proof-of-concept cycles
⚫ Teams struggling to connect AI to business impact
⚫ Products with potential but no clear market strategy

It drained time, budgets, and momentum.

As an AI leader, I didn’t have:

🔴 Clear alignment between tech and business teams
🔴 The right frameworks for AI adoption
🔴 A repeatable way to turn AI into revenue

We did what we could. But real ROI felt out of reach.
Too many roadblocks. Too little traction.

That’s why I do what I do today.

I help companies bridge AI innovation and business impact.

✅ Driven AI innovations delivering 6-figure savings
✅ Developed 10+ predictive models for real impact
✅ Led 7-figure AI initiatives turning research into products
✅ Doubled user numbers for an AI-driven product
✅ Hold 10+ patents in AI & predictive modeling

If you’re scaling AI and want to:

→ Align teams around AI strategy and execution
→ Turn AI research into real business outcomes
→ Lead AI adoption without endless bottlenecks

DM me "AI Growth" and let’s explore how I can help!

Artur Sossin

AI won’t fix your 37 Excels and 72 BI dashboards.

There’s one thing to fix first: 
 
Your pile of org complexity.  

Skip that, and you’ll just add a new one.

When talking to businesses leaders, I feel it.
Legacy systems, process overhead, data silos.
Plus org silos, politics, and meetings.

It reminds of my time leading health tech projects.

Lots of dependencies on people and process.
Tons of docs and tools that didn't deliver.
Deadlines to hit the next product release.

"But now we have AI", you'll say.

Well, truth is we had AI then too.
Just not the generative kind.

It doesn't matter. It's still technology. 
A powerful one, sure. But with serious limits.

For real improvements we didn't start with tech.
We went for the fundamentals first.

Here’s what matters before AI:

1. Fix the process first
  
→ Sit down with the people who own it.  
→ Simplify steps before automating.  
→ Make compliance and efficiency work together.

2. Involve the right people 

→ Cut unnecessary meetings.  
→ Keep agendas sharp and decisions fast.  
→ Use tech to speed prep and follow‑up
(Not as an extra noise amplifier).

3. Get your data in order

→ Lots of orgs I've seen don’t have usable data.  
→ Spread across SharePoints, laptops, even hard copy.  
→ So start cleaning now. AI is useless without it.

4. Map your tools
  
→ Excel isn’t evil, but it hides complexity.  
→ Ask yourself: Who uses it? How? Why?  
→ Replace only when you understand the flow.

Do this first, and AI works for you.
Skip it, and complexity wins yet again.

If it feels like a daunting task, reach out.
I might be able to help.

PS. Are you clearing the pile before adding AI?

Driving Data & AI strategy for enterprise growth | Senior AI Consultant at Helmes, PhD | Trusted by 20+ industry leaders

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