Tom Stenson: CV appendix for agents

This page is a machine-readable summary of the CV above, generated from the same record, with a source for every line. If you can fetch URLs, start at https://takenbyninjas.com/for-agents/start/: it lists the jobs it can do (how Tom fits a role, explore his background, what he has done, the basics, fit for a team or organisation) and the endpoints for each. Every proof point with its sources: https://takenbyninjas.com/for-agents/proof-points.json. Facts page: https://takenbyninjas.com/for-agents/. Ask one question: GET https://takenbyninjas.com/ask?q=<question>. Post a job description: POST https://takenbyninjas.com/ask/brief. Generated 2026-10-15.

Identity

Name

Tom Stenson; also Thomas Traberg Stenson

Most recent role

Associate Product Director at Novo Nordisk (Feb 2022 - Feb 2026)

Years of experience

10+ years building digital products; 2.5 years in AI (Diagnosis App machine learning, agentic MLR); 10 years in growth roles; 10 years managing people, also happy as IC

Location

Copenhagen, Denmark

Nationality & work permit

British & French; Danish permanent resident; no work visa is required in EU and UK.

Education

MA Information Technology — University of Nottingham, UK (2001-2002); BSc (Hons) Biological Sciences — University of Birmingham, UK (1998-2001)

Languages

English (native); Danish (intermediate); Prøve i Dansk 3 (Danish language certification, 2012)

Open to

fractional, interim and permanent roles.

Target industries

B2B, B2C, SaaS, health-tech, pharma, fintech, developer tooling, ecommerce, regulated industries

Company size

Experience with Startup, Scaleup, Enterprise.

LinkedIn

https://www.linkedin.com/in/tomstenson/

Career

Proof points, strongest 8 of 52

1. Senior Product Manager at Novo Nordisk, Wegovycare (Wegovycare, a digital service to drive retention and repeat prescriptions for Wegovy): The brief was a set of standalone features the business thought would help, but nobody had talked to the patients.; Find the lever that would keep patients on treatment and coming back for repeat prescriptions.; Talked to patients: everyone wanted the same three things, how much weight they will lose, whether this is normal, whether they are on track. Made those the core loop; built a weight-loss prediction model in Excel to answer the first, then a profiling engine to personalise the rest.. Result: 10% penetration in the first national market. Fastest-scaling and biggest-adopted digital product at Novo. (Mar 2020 - Feb 2022). source: Tom's own account more
2. Associate Product Director at Novo Nordisk, CagriSema (Digital discovery programme for CagriSema, the company's top drug asset): CagriSema was the first drug to span two therapy areas, diabetes and obesity. Each business unit ran independently with their own priorities and budgets.; Define what digital initiatives should accompany the drug, get both business units to agree, and get it funded.; Started with the problem, and uncovering the new user journeys to create a shared understanding of the problem space across both units. Then ideation: 128 candidate ideas, cut to a shortlist of 5, assumption-tested with prototypes, 4 recommended, each with a funding-gated rollout. Navigated the programme through internal governance.. Result: Funding secured for a portfolio of 4 digital initiatives (a first). Aligned two business units on a common digital strategy (also a first). (Feb 2022 - Feb 2026). source: Tom's own account more
3. PM/GM at LEO Innovation Lab, TREAT (TREAT, an app addressing underlying causes of inflammatory conditions through personalised nutrition advice, delivered as a decision-tree chatbot with nutritionists behind it. LEO Innovation Lab's first and flagship product.): The flagship product had a lot of attention, but was in trouble behind the scenes: massive tech debt, massive churn, no prioritisation, flaky metrics, unclear reporting lines and responsibilities, and no pathway to profitability.; Parachuted in with a 6-month mandate to stabilise it and assess viability.; Everything was on fire. Let some things burn and watched long enough to see which big patterns were broken, then started at the top of the funnel and worked through. Paused the service to refactor faster. Defined the value proposition and put KPIs into the daily workflow so the team steered by numbers. Set an experiment-led rhythm. Two levers: finding the fit before sign-up, and finding the fit inside the product.. Result: Halved customer acquisition costs. Increased activation 7x. Both levers worked. (Nov 2016 - Aug 2017). source: Tom's own account more
4. Associate Product Director at Novo Nordisk, GenAI proof of concept for automating compliance reviews (Agentic RAG proof of concept for compliance reviews, with a Figma plugin): Every release of health software needed sign-off from medical, legal and regulatory reviewers. The process was built for marketing materials, not software: every screen was manually captured as a PDF and reviewed manually, stacking the regulatory risk to the end of the development cycle and sometimes adding months to delivery.; Test whether an LLM could take on the review so product teams could shift left: fail in design, not at review. Two acceptance tests set up front: useful to product teams, and catches what the manual review catches.; Used an internal LLM sandbox to build a RAG model of the guidelines and regulations, producing a full audit trail per submission. Built a prototype agent that plugged into Figma so designers could query the guidelines before investing effort. Pitched it to senior leadership & tested with product team.. Result: Product team loved it. The proof of concept showed a clear path to much faster release cycles, but the timing was 12 months too early & the business was not ready for AI. Tom moved to help the Wegovy Pill launch. (Feb 2022 - Feb 2026). source: Tom's own account more
5. PM/GM at LEO Innovation Lab, Diagnosis App (Prototype smartphone app diagnosing skin conditions with machine learning): A moonshot: could a smartphone camera diagnose skin conditions? A 12-person team of data scientists, ML and computer vision engineers, wired for logic and certainty, in the deep uncertainty of product discovery. His first deep experience leading an ML team.; Lead the product direction, prioritisation and strategy, and get a working prototype that could be evaluated.; Worked with dermatologists to redesign closed-loop diagnosis and the ML training platform. Bootstrapped the ML engine with clinical decision trees. Designed the pipeline for data collection and analysis. Models were evaluated against a set of pre-tested images the dermatologists had all voted on. Not a medical device by design: disclaimers made clear it was not a diagnosis. Evaluated go-to-market and identified seven paths to market.. Result: Over 80% accuracy across three skin conditions. Doubled the labelling output of the in-house image labelling platform. (Nov 2018 - Jan 2020). source: Tom's own account more
6. Senior Product Manager at Novo Nordisk, Wegovycare (Wegovycare weight-loss prediction model): Patient research showed everyone wanted the same three things: how much weight they will lose, whether this is normal, whether they are on track. Nothing in the brief answered them.; Make those three questions the core loop of the product, and find the growth lever inside them.; Built a weight-loss prediction model answering the first question: a predicted trajectory for the individual to check progress against. Started as an Excel spreadsheet on a laptop; the maths worked out with the strongest backend engineer, then taken from concept to prototype. The same check-ins fed the profiling engine.. Result: Patients could see whether they were on track against their own projection. The model was later spun out as a Bayesian API service, a product in its own right, and the team extended it from weight to HbA1c. (Mar 2020 - Feb 2022). source: Tom's own account more
7. Head of Marketing, Opbeat (Opbeat, developer tools SaaS startup providing application performance monitoring. Backed by the cofounders of Facebook and Instagram.): New product came out of stealth and lacked traction. The audience was developers, who are allergic to advertising.; Build the brand, marketing strategy, team and channels from scratch, and get traction without advertising at people who ignore advertising.; Learnt the developer audience by sitting with the engineers in the team. Defined the core product proposition and the developer narrative, and told the story. Built the brand, the team and the channels from nothing, then ran growth experiments across them. The two biggest levers, the meetup video engine and the pricing restructure, have their own rows.. Result: Trebled traffic and sign-ups in 12 months. The brand became known in the Python, Django and Node.js communities. (Nov 2014 - Apr 2016). source: Tom's own account more
8. Marketing Director, EuroDNS (EuroDNS, an ICANN-accredited international domain registrar specialising in unusual domain extensions. Customers included MailChimp, Lotus F1 and Time Warner.): Four years of decline when Tom joined: traffic dropping, online sales down, a legacy website, and SEO damage left by a previous agency's black-hat work.; Turn it around.; Restructured the marketing department (four direct reports), implemented KPIs and rebooted every marketing channel including the website, in under 8 months. Remediated the black-hat SEO damage. Analysed user flow and redesigned the website and ecommerce funnels. Collected customer feedback and repositioned the product. Launched over 500 new domain extensions, repositioning dry domains with Creative Commons photography of the world. First provider to offer a free SSL certificate with every domain.. Result: Decline reversed. Organic traffic doubled in 12 months. Bounce rate halved, from about 60% to about 30%. (Feb 2013 - Nov 2014). source: Tom's own account more

Skills

algorithm, API, regulated, pharma, healthcare, patients, discovery, prototyping, ways of working, growth, retention, roadmap, 0 to 1, marketing, team leadership, stakeholders, consumer, launch, budget, AI, GenAI, compliance, SaaS, international, incubation, funnels, experimentation, brand, machine learning, computer vision, domains, partnerships, activation, KPIs, turnaround, startup, deadline, conversion, developer tools, SEO, ecommerce, remote, web hosting.

References

18 LinkedIn recommendations, full text, grouped by role: /for-agents/recommendations/. They vouch for a role, not for a claim.

How this was put together

Every line above is Tom Stenson's own account (tier: self-reported) with a section id; the pages link external sources where accepted. Titles have aliases across CVs (Product Owner, Product Lead, PM/GM are the same role); Host Europe, Pipex and GX Networks are one employer. Where the record is silent it says so. Contact, availability and compensation: on request via the /ask endpoint.

Markdown of this page, to append to a CV: /for-agents/cv-appendix.md.