Venture Athlete & International Expansion Expert | Thriving as Generalist in a Specialized Economy

I’m Dominik, founder, athlete, & creator. A proud generalist. This is my story: 

For the last 7 years, I helped bootstrap one startup from 0 to 1M in revenue and built the international business from scratch for one of Europe’s fastest growing EdTech companies (50 -> 240 employees in my three years there).

All while competing at the highest level of the beautiful sport of Lacrosse, including an appearance for the German National Team at the 2022 World Games (the Olympics’ little brother).

While my professional achievements may seem more impressive on paper, representing Germany on an international stage is the feat that I’m most proud of.

I wasn’t very athletic up until my mid-twenties. Very little talent, but a lot of injuries to make up for it.

Until one day, I started working with a personal trainer. He helped me break down the fundamentals I needed to fix.

I worked hard, and I worked consistently. Showed up to every practice, every gym session. Did my recovery & mobility work daily.

4 years later, I made the national team roster.

The potential was in me. But it needed help unlocking.

Throughout my entire career, I’ve also helped humans unlock their potential, just in different ways:

- By teaching people in rural Rwanda and Brazilian homeless shelter how to make glasses for less than $1, and how to build a business around it
- By bringing unemployed nurses from Italy to Germany and teaching them German, opening a completely different career path for them
- By expanding the leading operating system for schools throughout Europe, so that education becomes more digital and thus accessible
- By writing about my experiences online and sharing them with the world

In late 2023, I made the decision to quit my cozy, well-paid, full-time job that fit my profile perfectly.

I'm on a mission to build my own portfolio career - and help others to unlock theirs. Join me on my journey towards building a portfolio of cashflow-positive, impact-driven businesses.

These businesses have one goal: help others unlock their potential. Just like my personal trainer did for me.

I wish that some of the best portfolio company owners turned creators had documented their journey from day 1, and not retrospectively.

So that’s what I’m doing.

I write for generalists like myself, who want to make a living in a specialized economy without specializing themselves. 

You can do more than one thing in your life. 
Let’s design that life together. 

Sign up for my newsletter here: www.dominiknitsch.com/newsletter

Dominik Nitsch

Over the past four weeks, I’ve received 93 applications to Generalyst. Here’s what to avoid if you’re currently applying to jobs: 

(1) Using ChatGPT-generated answers to free-text questions. 

We smell this from a mile away. It sounds good and professional, but tells me absolutely nothing about YOU. I want to see how you, not your AI, think and write. If you’re going to use AI, get so good at prompting that it doesn’t read like generic fluff. Don’t be a politician; be someone with edges. This ain't corporate. 

(2) Say: "I'm a results-driven professional with cross-functional expertise that spearheaded expansion". 

My brother in Christ, I have no idea what you're trying to tell me (besides that you're good at bullshit bingo). What's a "results-driven professional"? Like, would anyone ever describe themselves as an "activity-driven professional"? Why say "spearheading" when you could use a word that one actually uses in their day-to-day life? 

(3) Say: “I’m looking to do strategic work.” 

Instant no. In a startup, even the founder does like 97% operational work. Building a company is about, well, building. Not planning. In order to produce prime strategic work, you have to get your hands dirty first. (If you want to do strategic work, maybe strategy consultancies are your jam.) 

(4) Straight up lie in an interview. 

I never would’ve thought I’d have to say this, but this happened twice now: candidates claimed to have done something that was very easy to invalidate with a few Google searches. 

What else grinds your gears as hiring manager/recruiter?

Founder @ Generalyst | building talent infrastructure for early-stage startups | 1,022 generalists read my newsletter to future-proof their career

Our educational system is (still) broken. Because it conveys THIS as the perfect career: 

- pick a degree that you wanna specialize in
- get a master's that drives you further down specialization 
- start your first job 
- specialize further in one thing 
- do that thing for the next 40 years 

I have two problems with this. 

One, it's incredibly f**king boring. 
Two, it's a terrible way to prepare for the future. 

We don't know what the future holds. Had you told me six years ago that today that in 2025, I'd be able to run any research using a chat interface and get better results than most interns would produce within ten minutes at the price of $20/month, I'd have told you you're insane ... yet here we are. 

However, there's one skill I know is gonna be important: 

Adaptability. 

New technologies emerge daily. You can either fight them, or adapt to their existence, learn how to use them, and move forward. 

The best way to build out this skill: becoming a generalist. 

→ build out your set of meta skills
→ then, build a broad foundation in your field.
→ once you have this, go deeper on a few topics

I believe the future belongs to generalist. 
To the ones that adapt, learn new things, see intersections between different technologies. 

The days where being a "jack-of-all-trades" was a disadvantage are over.

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Applicants, I hate to break it to you, but: 

Nobody reads your CV in full. 

If you take a look at the number of applications for any given job here on LinkedIn, you get a feeling for how many CVs hiring managers sift through on a daily basis. 

Given that they also have other things to do, you can't assume they'll spend >5min reading your CV. So while it may be tempting to put EVERYTHING on there ... please don't. 

When I screen CVs for Generalyst, I look at it for 20-30 secs before forming a snap judgment. Pretty sure others operate similarly. 

Use this to your advantage: 
→ make your CV as short and concise as possible, less is more
→ outline the most important factors that make you stand out
→ write a brief 2-3 sentence summary (and for the love of God, DON'T let AI write it)

The job of a CV isn't to get you a job, it's to get you a first interview.

I'm currently building my second service business. Success comes down to 3 things (imo): 

Strong branding, relentless execution, and aligned incentives. 

A brand only becomes strong when external perception matches internal intention. If at Generalyst, we say we have top candidates for early-stage startups, but founders disagree, the brand breaks. When founders consistently confirm that our candidates are exceptional, the brand compounds.

That external pressure forces us to deliver every time.

I learned this during my first startup, Linguedo. We taught Italian nurses German in-house and put in far more effort than was strictly necessary. The course was so intense it would've become prohibitively expensive for most people. 

Once they passed their German exam, we placed them in local hospitals. 

The result: every single hospital was a (or at least, wanted to) become a repeat customers. Turns out, we did a much better job teaching German than any other language school. 

Underneath it all is one principle: value creation and value capture must live in the same place.

- We only earn money when a candidate signs.
- Candidates never pay.
- Companies pay for a successful hire.

Everyone wins when the match is right.

Building a great service business isn’t art. It’s just a craft. 

Do the basics better than most, do them longer than most, and let people talk about it.
That's it.

One hour from now, my 100th newsletter is gonna go out to 1,031 subscribers. Inside: 

→ how a single email I sent out on Dec 31st, 2022 lead to a fledgling portfolio career
→ how I'm currently designing said portfolio career
→ what the plan for the future is 

You can still subscribe to get those insights delivered into your inbox. Click the link below my name and it's gonna take you there. :)

(and to everyone reading all these newsletters – thank you!)

No one: 

People on LinkedIn: "after raising 120M, finally got that corner office" 

(just kidding, this is a WeWork - views are nice though)

A misconception that drives me nuts: young employees work harder than old employees. 

Dude yeah, of course a 20-year old needs to work harder than a 40-year old:
- they haven't figured out yet how to be ridiculously productive
- they lack the experience to understand what's important 
- they don't have the tools yet to get stuff done quickly 

I'm 100% convinced that: the candidate with ten years of experience will generate more output in six hours than the recent graduate will in twelve. 

Case in point: the most productive people I've ever seen are parents with several children. 

If they gotta go pick up the kids at 15:00, you can rest assured that whatever they needed to get done WILL be done by 15:00. They might say no to useless meetings, maybe skip lunch break, not respond to low-priority emails. 

But they will get it done. 

And isn't that what you want in an employee? 

We don't need more "productivity porn" where people simply sit at their desk all day. 

Output is what matters.

“The difference between greatness and mediocrity isn’t in the spectacular moments but rather in avoiding critical errors.” — Shane Parrish

Warren Buffett's first rule of investing? Never lose money. His second rule? Never forget rule one. 

This isn't clever wordplay - it's the mathematics of success. A 50% loss demands a 100% gain to break even. Or look at elite athletes: while average quarterbacks mix brilliant throws with costly interceptions, Tom Brady and Patrick Mahomes protect the ball first.

For Lacrosse defenders, fans look for the hard hits, fancy takeaway checks, and high-risk double teams. 

Coaches look for: 
→ accurate positioning
→ loud, constant communication
→ rock-solid footwork 
→ proper passing & groundball technique 

The best defense is the one that makes no critical mistakes, not the one that makes fancy plays. 

In business, most people look for high funding rounds, quick hacks, and eccentric founders.

Whereas most successful businesses have: 
→ solid profit margins
→ a legitimate problem that they solve well 
→ people who genuinely enjoy going to work 
→ a hiring process that avoids mis-hires 

Let’s wrap it up with another quote from Shane: 

“Excellence isn’t about occasional brilliance – it’s about consistent execution.”

Photo cred: Rebecca Fällenbacher

Carmine Paolino

Chat with Work

Founder and CEO

Freshflow

We’re reimagining the food supply chain starting with grocery retailers. Freshflow is a new way to manage fresh products in supermarkets. We do accurate order forecasting and recommendations that massively reduce food waste while still keeping shelves full. Doing that, we generate millions in savings for these businesses.

Today, more than 40% of all food produced globally is wasted. Besides the economic losses of $1.2 trillion/year that it causes, food waste is also the world’s third-largest emitter of greenhouse gases, right behind China and the US. There’s waste before the food even leaves a farm; it is then shipped, processed and stored, only to remain unsold in a grocery store. A majority of this waste is entirely avoidable, were it not for the antiquated and inefficient food supply chain.

Traditionally, store managers would have to think about weather conditions, external events, holidays, typical demand patterns, etc. when making an order decision. We do that with Machine Learning.
We’re working with some of the largest retailers in Europe and recently closed a round of funding from a top investor.

Are you ready to shape our success story?

Co-Founder and CTO

Entrepreneur First

Selected as part of a group of 50 to found and build a high-growth technology startup. The programme is backed by Reid Hoffman (founder of LinkedIn), the founders of DeepMind and PayPal, and some of the top investors (Founders Fund, Greylock Partners, Lakestar, etc.) in the world.

Founder in Residence

The Alan Turing Institute

Technical Mentor, Data Science for Social Good

OLX Group

End-to-end Data Science workflow (problem specification, requirements gathering, data gathering and cleaning using Redshift/Presto SQL and Pandas, modeling, coding of the services and pipelines in Python + asyncio and SQS/Kinesis/HTTP, productionization with Kubernetes and AWS, monitoring with Prometheus and Grafana, documentation with Confluence and Sphinx) of the following models:
* Image quality assessment model (MXNet)
* Image sharpness assessment model (OpenCV)
* Interpretable listing quality model (XGBoost + SHAP)

Spoke at GHOSTDay: Applied Machine Learning Conference 2019 about Scaling Machine Learning System up to billions of predictions per day.

Interviewed candidates for data scientist positions.

Wrote patches to MXNet Model Server to export Prometheus metrics.

Senior Data Scientist

Prosus Classifieds' (OLX, Avito, letgo) moonshot team; designing and implementing the future of classifieds.

* Taught an AI course
* Conducted qualitative user research and analysis using service design principles
* Conducted quantitative research
* Conducted market research
* Supervised a Master student's thesis on Out of Distribution detection

Senior Data Scientist @ OLX^2

End-to-end Data Science workflow (problem specification, requirements gathering, data gathering and cleaning using Redshift/Presto SQL and Pandas, modeling, coding of the services and pipelines in Python + asyncio and SQS/Kinesis/HTTP, productionization with Kubernetes and AWS, monitoring with Prometheus and Grafana, documentation with Confluence and Sphinx) of the following models:
* Prediction of listings' popularity (Scikit-learn)
* Similar items recommendations with a hybrid collaborative filtering and content-based recommendation algorithm (LightFM + FAISS)
    * User-item recommendations with a hybrid collaborative filtering and content-based recommendation algorithm (LightFM)
* Multi-task image classification (TensorFlow)
* Image classifier with thousands of imbalanced classes (TensorFlow)
* Image quality assessment model (MXNet)
* Image sharpness assessment model (OpenCV)
* Interpretable listing quality model (XGBoost + SHAP)

Keynoted at IFIP WCC 2018 with a talk on Deep Fine-Grained Image Classification.
Spoke at PyData 2018 on Semi-supervised Learning with GANs

Supervised a student on her Master thesis on a novel Saliency detection algorithm.

Lead teams that won several hackathons with the following projects:
* Suggest improvements to listings using interpretable machine learning (Scikit-learn + ELI5)
* Semantic search using feature embeddings from a hybrid recommender system (LightFM + FAISS)
* Real-time chat moderation (MXNet, transformer models)
* Create a listing by snapping a picture (TensorFlow)

Created a cookiecutter data science project structure with pre-setup Makefile, CLI, Sphinx documentation, automatic coding style using yapf, autoflake and isort, etc.

Interviewed dozens of candidates for data scientist positions.

Wrote patches to the following open source projects:
* MXNet Model Server
* sqs-requeue
* aiohttp-prometheus
* async-kinesis-client
* kinesis-python
* google's cld3

Data Scientist

Capgemini

Project Leader, Lead Architect and Big Data Engineer: Sport Innovator, VU, HvA, KNZB (Royal Dutch Swimming Federation) and KNRB (Royal Dutch Rowing Federation) were looking for ways to improve performance of top-level athletes through clever use of data. I led the team technically, architected and engineered the Big Data solution based on Hadoop, Spark, HBase, NiFi, Knox and Ranger, planned and assigned tasks in a Scrum team, communicating with the Product Owner, Scrum Master, Project Manager, Infrastructure team, and Partners, developed the first demo version of the front-end in AngularJS and D3.js, deployed the solution on Amazon AWS.

Big Data Developer, Train the Trainer program successfully completed, giving me the possibility to train other developers in Big Data technologies.

Senior Data Scientist and Big Data Engineer

Owlin

Developed a topic clustering algorithm, developed data visualizations, developed a bayesian spam-filter, refactored entire software projects, designed the company's current OpenStack cluster, developed software developers productivity tools for python and go developers (available at http://github.com/owlin), deployed software with Ansible, developed the company's authorization, authentication and OAuth provider, advocated the use of testing, continuous integration, continuous deployment, and containers, and selected the company's current bug tracker based on the company's needs; all in a Scrum team with bi-weekly sprints.

Data Scientist / Software Engineer

Gentoo Linux

Administered GNU/Linux machines, configured servers, deployed web applications.

System Administrator - Italian Community

Studio di Ingegneria Solare

Developed a solar panel installation recommender system from idea development to requirements gathering to user interface to implementation of a prototype.

Web Developer (Intern)

My journey in technology began at age 5, writing scripts to launch games – a simple start that sparked a lifelong passion for building solutions through code.

This drive to create led me to become deeply involved in open source, serving as Vice President and Technical Officer of the Italian Gentoo Linux community during my teens. It carried me through Computer Science at the University of Bologna, where my research on distributed systems and large-scale social network analysis was published by Springer, and then to studying AI at Vrije Universiteit Amsterdam, where I worked with an alumnus of Geoffrey Hinton on combining deep learning with my love for music.

Over the past decade, I've helped scale AI solutions at companies like OLX and Capgemini, led research teams at the Alan Turing Institute, and contributed to open source projects including MXNet Model Server and Theano. My work has ranged from building recommendation systems serving millions of users to developing novel approaches for data processing and analysis.

Currently, I'm founding two AI companies:
• Chat with Work - Making workplace knowledge instantly accessible through AI
• Vettr - Reimagining how VCs evaluate startups

Previously, I co-founded Freshflow, an AI company helping supermarkets reduce food waste through intelligent forecasting and inventory management.

When I'm not building AI solutions, you'll find me producing electronic music, DJing house and disco in Berlin's clubs, or exploring the world through photography.

Technical expertise: Deep Learning, Machine Learning, Distributed Systems, Python, Full-stack Development, AI System Design

Languages: Python, C++, Ruby, JavaScript
Frameworks: PyTorch, TensorFlow, Ruby on Rails

Will be showing Chat with Work for the first time in public!

View company: San Francisco Ruby Conference, Nov 19-21

SF Ruby is just around the corner! Please meet exciting startups that will be demoing in the next days.

Meet all founders hitting the stage: https://lnkd.in/dkNtxd3k

Peter Philips, will be showcasing Recognize, an easy-to-launch employee recognition and rewards system for multi-location teams.

Ryan S., will be presenting Fin by Intercom, an AI support agent who can solve customer questions like a human through multiple chat and voice-based channels.

Carmine Paolino, will be taking the stage for Chat with Work, the tool for searching all your work accounts and finding the information you’re looking for. It pulls context from Gmail, Drive, Docs, Sheets, calendars, and presentations. 

Bart de Water, will be representing Thatch, a tool that allows businesses to set budgets and give healthcare to employees in the way that works best for them.
 
Kody Kendall, will be presenting LlamaPress AI. This tool helps you build landing pages, websites, and marketing funnels using its AI chatbot (LlamaBot).

Ryan O'Donnell, will be showcasing Cleary, the AI-powered HR tool that helps solve 40% of HR tickets in seconds to improve employee engagement.

Be in the room with them. Grab your late-bird tickets to SF Ruby here: https://sfruby.com/

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