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Goodnotes
London
Source: Goodnotes careers · View original posting
From Goodnotes's posting. “We” and “our” refer to the employer.
Good Systems is the parent company behind Goodnotes, where millions of people capture and develop their ideas.
Goodnotes is where we started, and it’s now the foundation for a growing family of products. By reimagining how we interact with information, we’re bringing together human creativity and the breakthrough capabilities of AI.
We build products that help people turn good thinking into good work.
Our Values
Dream big
Think of this as a startup within Goodnotes. You'd be embedded in one of our 0-1 product bets -working directly with Steven, our founder, and a small, fast-moving team building something genuinely new inside Goodnotes' AI-native product line. No legacy roadmap, no established playbook. You're helping write the first one.
You'll be the analytical partner for that product: quantifying how features move the business, building the experimentation and instrumentation that lets the team measure impact from day one, and turning ambiguous, undefined problem spaces into clear questions and confident decisions. In a 0-1 environment, that clarity is the difference between shipping the right thing and guessing.
You'll combine analytical precision with product intuition - designing experiments, uncovering the behavioural drivers behind conversion, activation, and retention, and connecting product metric movements straight back to revenue.
Crucially, you won't just do the analysis. You'll build the frameworks, playbooks, and self-serve capability that let the product team answer their own questions — the kind that hold up when you're not in the room. Removing analytics as a bottleneck isn't a side goal here. It's part of the job.
This role is based full-time onsite at our London (Paddington) office
This role is a fixed term contract of 1 year
This is the role for you if you're excited to work on:
Partner with GTM, Product, and Engineering to set success metrics, size opportunities, and connect product metrics to revenue — ensuring every team knows what "good" looks like.
Design and analyze experiments with statistical precision, standardize how experiments run across squads, and help the organization move from opinion-driven to evidence-driven decisions.
Work with Engineering on tracking plans and event taxonomy so features are measurable before they ship, not retrofitted after.
Run deep-dive analyses on funnels, cohorts, activation, and retention, and translate findings into actionable recommendations that drive product and business outcomes.
Teach PMs and product leaders to read experiment results and governed reporting with confidence. Build frameworks others can adapt and extend — reducing the analytics team as a bottleneck.
Proactively surface the questions the product organization should be asking before they're asked, and know when a finding is sufficiently reliable to drive action.
knowing when a finding is sufficiently reliable to drive action, avoiding the trap of pursuing endless granular accuracy.
Significant experience of product analytics in a PLG SaaS, marketplace, or transactional environment. You understand funnels, retention curves, user lifecycle, and how product metrics connect to revenue.
Deep experimentation experience. You’ve designed and analysed experiments, and you know the common failure modes (peeking, underpowered tests, bad randomisation, metric gaming) and how to design around them.
Strong instrumentation and data governance instincts. You’ve defined tracking plans, and worked with engineering teams on event taxonomy.
Experience working in AI-native product orgs. You’ve gone past chatting with Claude/ChatGPT to building proactive agentic workflows that scale insights discovery and delivery with minimal human intervention.
Strong SQL plus Python and/or R – you write queries and build analyses yourself, regularly.
A track record of building frameworks others adapt and extend. You make teams smarter, not just yourself heard.
Excellent communication, you adapt your altitude to the audience
Comfort operating in ambiguity with autonomy.
Familiarity with dbt, semantic/BI layer, and governed self-serve stacks (Hex, LightDash, Looker, or similar)
A conversation with our Talent Acquisition team to dive into your experience, what motivates you, and why you're interested in joining Goodnotes.
A deeper dive into your professional background, your preferred ways of working, and the specific impact you'll have within the team.
As an AI-first company, you'll meet with one of our AI champions to discuss your curiosity, understanding, and practical use of AI tools in your daily workflow.
At-Home Case Study
: A take-home exercise to help you prepare for your live Role-Specific Assessment — you'll receive this in advance so you can work through it at your own pace.
A live session building on your case study, focused on the core technical and functional skills required for the role. This is your chance to walk us through how you tackle real-world challenges. This will take place onsite in our Paddington office.
A conversation with 2–3 team members centered on our company values. We'll discuss past experiences to see how your approach aligns with our culture.
We provide dedicated stipends for the things that keep you at your best, including noise-canceling headphones for deep focus, professional training, personal development, and health and wellness activities.
While we embrace flexible work, we love seeing each other. We provide sponsored visits to our beautiful office locations to foster face-to-face collaboration.
Once a year, we gather the entire global team in person to celebrate our wins, align on our vision, and build lasting connections.
Your well-being is our priority. We offer premium medical insurance for you and your dependents to ensure peace of mind for your whole family.
Goodnotes is committed to fostering a diverse, inclusive, and equitable workplace. We welcome applications from individuals of all backgrounds, identities, and experiences, making all employment decisions based strictly on merit, qualifications, and business needs.
Note: Employment is contingent upon successful completion of background checks, including verification of employment, education, and criminal records.
Applies when submitting through the employer's application site.
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