At a Glance
- Tasks: Join a fast-paced team to redefine digital note-taking with AI-driven insights.
- Company: Goodnotes, a visionary tech company focused on innovation and user empowerment.
- Benefits: Enjoy growth budgets, health coverage, and global connectivity with your team.
- Other info: Collaborate directly with the founder and build frameworks for self-service analytics.
- Why this job: Be part of a startup-like environment, shaping the future of productivity and creativity.
- Qualifications: Experience in product analytics, experimentation, and strong SQL skills required.
The predicted salary is between 60000 - 75000 £ per year.
At Goodnotes, we believe that every individual holds untapped potential waiting to be unleashed. By reimagining the way we interact with information, we’re merging human creativity with the breakthrough capabilities of AI. Our renewed vision and mission drive us to create the best medium for human and AI collaboration, empowering users to explore new dimensions of productivity, creativity, and learning. Join us on this journey as we transform digital note-taking into an inspiring and innovative experience.
Our Values
- Dream big: Be visionary, strategic, and open to innovation.
- Build great things: Work in service of our users, always improving and pushing higher.
- Operate like an owner: Take responsibility with bold decision-making and bias for action.
- Win like a sports team: Be trusting and collaborative while empowering others.
- Learn and grow fast: Never stop learning and iterate fast.
- Share our passion: Share ideas and practice enthusiasm and joy.
- Be user obsessed: Empathetic, inquisitive, practical.
About the role
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:
- Defining success metrics & sizing opportunities: 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.
- Building the experimentation practice: 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.
- Owning instrumentation & measurement quality: Work with Engineering on tracking plans and event taxonomy so features are measurable before they ship, not retrofitted after.
- Turning behavior into insight: Run deep-dive analyses on funnels, cohorts, activation, and retention, and translate findings into actionable recommendations that drive product and business outcomes.
- Enabling teams to self-serve: 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.
- Shaping the agenda: 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.
- Defining good enough: Knowing when a finding is sufficiently reliable to drive action, avoiding the trap of pursuing endless granular accuracy.
The skills you will need to be successful:
- 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).
Preferred:
- Experience in productivity SaaS businesses.
- Familiarity with dbt, semantic/BI layer, and governed self-serve stacks (Hex, LightDash, Looker, or similar).
- Causal inference methods beyond A/B tests.
- Experience implementing experimentation platforms (e.g. Statsig, Eppo or in-house).
- Familiarity with product analytics tools (Amplitude, Mixpanel, Firebase, or similar).
The interview process:
- Talent Intro Call: A conversation with our Talent Acquisition team to dive into your experience, what motivates you, and why you're interested in joining Goodnotes.
- Hiring Manager Interview: A deeper dive into your professional background, your preferred ways of working, and the specific impact you'll have within the team.
- AI Literacy: As an AI-first company, we'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.
- Role-Specific Assessment: 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.
- Values Based Panel Interview: 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.
What's in it for you:
- Customized Growth & Wellness Budgets: 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.
- Global Connectivity: 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.
- Company-Wide Offsites: Once a year, we gather the entire global team in person to celebrate our wins, align on our vision, and build lasting connections.
- Comprehensive Health Coverage: 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. By submitting your application, you acknowledge that you have read and understood our Candidate Privacy Notice, which provides important information about the data we collect during the application process.
Senior Data Scientist - Stealth AI (12-months Fixed-Term Contract – Renewable) employer: Goodnotes
Goodnotes is an exceptional employer that fosters a collaborative and innovative work culture in the heart of London. With a strong focus on employee growth, you will have the opportunity to work closely with the founder on cutting-edge AI-first products, while enjoying benefits such as flexible working arrangements and a commitment to professional development. Join us to be part of a dynamic team where your contributions directly impact the business and drive meaningful change.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist - Stealth AI (12-months Fixed-Term Contract – Renewable)
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We think you need these skills to ace Senior Data Scientist - Stealth AI (12-months Fixed-Term Contract – Renewable)
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Goodnotes, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Goodnotes, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Goodnotes’s attention and show the tangible impact of your work.
How to prepare for a job interview at Goodnotes
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Goodnotes.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Goodnotes.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Goodnotes.