I build innovation-driven teams, products and organizations. In my work I combine humanism, product design, AI/ML and business. Selected examples below.

Personalization and Recommendations, Search and Browse at Zalando (2022-)

Zalando Fashion Assistant
© Zalando SE 2023

Leading product design and working with multidisciplinary cross-functional teams to make Zalando’s customer experience more personalized and adaptive.

For example, our team is driving state-of-the-art innovation by combining product design with AI/ML and meaningful content in building Zalando’s smart Fashion Assistant. Additionally, recently the team turned a new strategic vision into a concrete product design direction leveraging emerging technologies and platform-driven approach. To achieve this, the team embraced multidisciplinary approach and facilitated new rituals and ways of working to effectively bring together product design, product management, data science, engineering, and business.

Zalando is Europe’s leading online platform for fashion and lifestyle, simultaneously being one of the continent’s top-tier technology companies.


Zalando to launch a fashion assistant powered by ChatGPT

22 product design learnings from 2022

A new journalistic AI/ML team, and its methods and tools for AI-augmented news acquisition at Yle News (2018-2022)

A new multidisciplinary function, team, and its methods and tools for AI-augmented news acquisition at Yle News (2019-)

My vision: journalists are augmented by machines in news acquisition, investigation and reporting.

Yle is the biggest news media company in Finland, and one of the leading public service media companies in Europe with the likes of BBC, NRK and ARD. Its headquarters is located in Helsinki.

🏋️‍♀️ Intrapreneurship in action: I built a multidisciplinary team and collaborative methods from the ground up to develop machine learning powered tools for news acquisition and investigation. The method is based on continuous multidisciplinary collaboration between journalists and data scientists resulting into a combination of human knowledge/curation and machine learning. I was also responsible for organising and securing the internal funding for the strategic development project.

“This is the best concrete thing that has happened to our journalistic development.”

A seasoned journalistic producer at Yle News & Current Affairs

Impact: the multidisciplinary method and its machine learning powered tooling concretely showed how the combination of journalism, data science and machine learning creates value for the newsroom and its customers. Significantly, the developed method allowed the team to uncover several international level breaking news stories in a short period of time.

🤔 Key learnings: 1) Journalistic organizations need a multidiscplinary product and design talent/leadership in-house. The combination of journalism, AI and design is needed in the newsroom, and in the development teams and leadership teams alike. 2) In order to renew journalistic organization, new journalistic roles and processes have to be co-designed and co-created in the core of the newsroom (e.g. our team introduced completely new roles of journalistic data producer and journalistic data scientist). 3) Sustainable and future-proof development of the news media organization requires dedicated and systematic journalistic leadership with the up-to-date know-how on our developing media and information ecosystem. At the same time, the journalistic mission, values and goals should guide all prioritization, talent acquisition, team-building and development work.


Yle News Lab builds a method that makes the power of social media visible 

Machine learning courses for journalists with London School of Economics’ Polis and Google News Initiative (2020, 2021)

Machine learning courses for journalists with London School of Economic’s Polis and Google News Initiative (2020, 2021)

🏋️‍♀️ Helped to create practical machine learning courses for journalists (in 17 languages) as a part of an international multidisciplinary team consisting of journalists and data scientists.

Introduction to Machine Learning for journalists 

Hands-on Machine Learning  

“This Introduction to Machine Learning is built by journalists, for journalists, and it will help answer questions such as: What is machine learning? How do you train a machine learning model? What can journalists and news organisations do with it and why is it important to use it responsibly?”

Mattia Peretti, JournalismAI. London School of Economics and Political Science, Polis.

Impact: the basics of how machine learning can help journalists now available and easily accessible in 17 languages wherever you are.

🤔 Key learnings: 1) There’s a growing need in the field of journalism to understand how machine learning can concretely benefit journalism and its goals. 2) Ensure that the course is a journalism-first, not a tech-first experience.

Troll Factory — an award-winning educational experience about information operations (2019)

Troll Factory — an award-winning educational experience about information operations (2019)
© Yle News Lab

Troll Factory edugame promotes media literacy by combining genuine social media examples with a gamified storytelling experience. The experience is personalized based on the player’s choices.

🏋️‍♀️ An intrapreneurial approach: built and led a multidisciplinary team from ideation of the initial concept to public launch for two localized versions of Troll Factory experience. Secured internal funding and executed all media reach-out.

Try it out here and (FI).

“‘Troll Factory’ puts you inside the seedy word of professional bull**** artists for a good reason: to help you spot misinformation when you see it.”

Mark Sullivan, Fast Company

“Troll Factory is sort of a choose-your-own adventure. You win by becoming the most malicious online troll. It’s a simulated smartphone screen…

I realized that the more I dial up the outrage, the more successful I become as a troll. The fake story really gets things going. My score surges. When I finish the game, I’ve hit 1,500 followers. They shared my post 14,000 times. I win the title director of disorder.”

Shannon Bond, NPR

Impact: Troll Factory has got significant international traction and it has already been played in over 100 countries across the globe. Among people using Troll Factory are professionals working with younger people—from public libraries to universities, schools and other educational institutions—students, media researchers and journalists as well as national security and cybersecurity professionals, who are interested in using Troll Factory as an educational material.

🤔 Key learnings: 1) The reporting on information warfare is comparable to war and catastrophe reporting. You need to show the raw reality to help people truly understand and comprehend the phenomenon. 2) In creating a personalized content experience, you need to test and iterate, and wash-rinse-and-repeat again in order to nail down the right rhythm and atmosphere. 3) This is a topic that can get under your skin. Focus on the communication and creating a psychologically safe environment inside the multidisciplinary team and magic can happen.

Selected coverage:


Fast Company 

Ars Technica





🏆 World Digital Media Awards 2020, Best Project To Engage Younger Audiences

🏆 European Digital Media Awards 2020, Best Project To Engage Younger Audiences

🏆 Global Youth & News Media Prize 2019, News/Media Literacy category

Five million political ads — targeted political advertising simulator (2019)

Five million political ads — personalized political advertising simulator (2019)
© Yle News Lab

Five million political ads simulator shows concretely how your choices and actions in social media (likes/faves/shares/comments etc.) can affect the political advertising you see online. The experience is personalized based on the user’s choices.

🏋️‍♀️ Intrapreneurship in action: built and led the team from concept ideation to public launch for a unique simulation experience for targeted advertising.

“A great innovation by Yle.”

Olli-Pekka Heinonen, Director General of International Baccalaureate

Impact: simulation experience received a great enthusiastic reception highlighting the need to make political advertising in social media more tangible and understandable. The experience was very frictionless as 92% of people starting the simulation completed it. Also, the user experience helped to concretely understand the dynamics of personalized content experience.

🤔 Key learnings: 1) Simplifying a very complex process of targeted political advertising was a great challenge for a newly formed multidisciplinary team. In this context, you need as a team to start by understanding the whole ecosystem—from political ideologies and their differentiating marketing messaging to the personalization methods used in social media—and then break it into comprehensible chunks for product design and development. 2) We wanted to create an experience that would let people without extensive background knowledge to understand the basics of targeted advertising. To achieve that, all complexity was hidden under the hood to mimic the people’s actual experience in social media.


Teimme vaalimainossimulaattorin, joka havainnollistaa, kuinka somekäyttäytymistäsi voidaan käyttää poliittisessa markkinoinnissa (FI)

AI-powered news assistant Voitto (2018)

AI-powered news assistant Voitto (2018)
© Yle News Lab

Voitto is the first smart news assistant in the world to appear and learn directly on your lock screen. The team set to create a human-centered and transparent personalization experience that would allow people themselves control how the news assistant works. The feedback loops for meaningful content recommendations had to be thought in a novel way to in order to let the user to interact with Voitto assistant directly on their mobile lock screen. Voitto’s user experience and its tone of voice in these interactions was a crucial element: news content can contain information that can be very emotional and even upsetting. Thus Voitto’s interactions were designed to work for varying news content recommendations, from sports results to big unexpected news events.

🏋️‍♀️ An intrapreneurial approach: built and led the team from ideation of initial concept to public launch, also securing the internal funding for the product.

“The Finnish broadcaster YLE has spent a lot of time thinking about these issues as it develops its Voitto intelligent assistant… [It] collects feedback on AI-driven recommendations directly on the lockscreen – the first app to do so – and aims to build an on-going dialogue with users about the choices they make.”

Nic Newman, Oxford Reuters Institute

Impact: the users of Voitto have been extremely happy about its user experience and recommendations. Over 90% of Voitto’s users have kept Voitto on, its personalized recommendations surfacing on their lock screen making sure they don’t miss the news that matter for them. The development of Voitto gave completely news insights on the possibilities of machine learning for adaptive user experience, happening outside of any app.

🤔 Key learnings: 1) The tighter the concept, the more streamlined the execution: Voitto was taken from a concept to production in less than 6 months. 2) An early end-to-end pipeline for machine learning, including potential feedback loops, helped to understand and iterate fast both recommendation models, user experience and metrics. 3) You need to figure out the right metrics for an AI assistant to really understand its user experience and overall impact.


First in the world: Yle’s smart news assistant Voitto ensures that you don’t miss the news you want to read (2018)

Ensimmäisenä maailmassa: Yle Uutisvahdin älykäs Voitto-assistentti antaa suosituksia suoraan lukitusnäytölle (FI)

Smart news assistant Voitto got quickly over 10k users (FI)


Oxford Reuters Institute’s Digital Trend Report 2019 

London School of Economics, Polis 

Läheltä / Near by — localized news recommendations and news alerts (2017)

Läheltä / Near by — localized news recommendations and news alerts (2017)
© Yle News Lab

Läheltä / Near by recommendations and their lock screen notifications are based on the users current or selected location.

🏋️‍♀️ Led the team from concept ideation to public launch for a completely new personalization function in Yle News.

Impact: Läheltä / Near by recommendations and notifications quickly gathered a strong growing user base. Also, as the recommendations and notifications could be hyper-localized (for example for only one small town), the product helped Yle’s local newsrooms to create a new direct and real-time channel and relationship with their local users.

🤔 Key learnings: 1) Content-first approach needed from the very beginning. 2) Newsroom support crucial for success: there won’t be useful recommendations without diverse local journalistic content. 3) Leverage the existing tech for its full potential.


Ainutlaatuinen palvelu kertoo nyt myös uutiset läheltä (FI)

Yle Uutisvahti / Yle NewsWatch revisited — productizing personalized news alerts and their adaptive content experience (2016-2018)

Yle Uutisvahti / Yle NewsWatch revisited (2016-2018)
© Yle News Lab

The team redefined how personalization and news alerts could be useful for news consuming citizens. These data-driven insights were turned into actual mini-products and features, including content-focused interactive notification products containing images and videos (e.g. Herätys/Morning briefing, Pääuutiset/Main headlines, Viikon kiinnostavimmat/Weekend briefing, Sää/Weather), frictionless personalized onboarding (Sinulle/For You concept), real-time big news event reporting based on news alerts (Juuri nyt/Hetki hetkeltä/Developing story), a notification monitoring system for newsroom and the first concise news alerts strategy for the Yle’s newsroom. 

I was also responsible in driving the development of a human-in-the-loop recommendation engine that used human input (for example in weighing news-worthiness as well as optimizing meta data) as a parameter in personalized news experience.

🏋️‍♀️ An intrapreneurial approach: built and led an agile multidisciplinary team to create an industry-defining news personalization experience by combining journalistic content, human curation, AI and adaptive user experience. 

Impact: in 2017, Yle Uutisvahti app became Yle’s fastest growing digital service simultaneously getting international recognition for its trailblazing personalization features and creative design of its content-driven notification products. The users of the app are very committed, and the app received at the time high ratings both on iOS and Android platforms. Additionally, the team created concrete ways for the Yle newsroom to understand the effects and impact of well-thought news alerts. Significantly, after the implementation of new news alerts products and strategy, the users of Yle NewsWatch considered the app’s notifications to be as useful as personal text messages.

🤔 Key learnings: 1) Even the most foundational innovations don’t matter if there isn’t enough resources to scale them in their full potential. 2) Personalization is never solved, but it’s a continuously moving target. You need a multidisciplinary approach to truly focus on the right things and to understand their potential impact for the user and the product. 3) Personalization should serve the content creation, and content creation should serve the personalization. Success.

Random, predictive discovery app & engine by Futuferul Inc. (2010-2015)

Random, predictive discovery app & engine by Futuferul Inc. (2010-2015)

Co-founded an internationally renowned startup that developed a pioneering AI-powered predictive media discovery experience and recommendation engine from the scratch.

🏋️‍♀️ I built and led the team, as well as worked as a co-founder to secure our pre-seed and seed funding from international investors. Additionally, I took care of the media relations, simultaneously leading the team from concept to multiple public launches.

“[Random] lets you browse the news in a different way to all the other news sites you’ve probably ever used.”

Kit Eaton, The New York Times

“Random never turns into a filter bubble, because it perpetually injects the irrational into my experience… in a cocktail of relevancy and serendipity.”

Claire Evans, Vice Motherboard

“Random… breaks you out by intentionally guiding you to new topics and interesting articles at sites you may not otherwise read.”

Alan Henry, Lifehacker

Impact: Random/Futureful pioneered in human-centric, filter-bubble-breaking content discovery, and was praised both by its users and international media on its minimalistic design and depth of diverse content.

By combining relevance and serendipity, rich media content, a deep machine learning system and adaptive user experience, Random turned into a product that could truly help people discover new things they didn’t even know existed.

Random’s innovative user experience solutions have later inspired the likes of Pinterest’s Guided Search, Snap’s Discover and Google Image Search.

🤔 Key learnings: 1) In a startup you don’t need a map, you need a compass in keeping your endeavour on the right track. With the compass you’ll find the right metrics to measure your true progress. 2) Iterate in short enough cycles. Don’t make your progress and growth dependent on massive releases. Also, don’t try to solve too many problems at the same time or you lose the focus. 3) Product is important, but the story is crucial for a B2C startup. Make sure you have enough resources to make the story heard. Bonus: as an early stage startup, hire hunger and enthusiasm, not experience or competence (obvious, yet not so obvious when you’re also doing deep engineering). Extra personal bonus: after doing field user research in the Valley in 2013 I was sure that the lock screen notifications, or news alerts, are the next important thing for personalization. Yet, I wasn’t effectively able to convince the team and push them to our product roadmap as the evidence of their coming significance was still too thin.


Random the app More: 


Selected coverage:

The New York Times 




Vice Motherboard 


Fast Company 


MIT Technology Review



The core-technology patent on predictive data objects is today referenced and cited e.g. by Google, Microsoft, IBM, Adobe and Amazon.