At a Glance
- Tasks: Join a dynamic 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 team offsites for collaboration.
- Other info: Work in a fast-paced environment with excellent career development opportunities.
- Why this job: Be at the forefront of AI innovation and make a real impact in productivity.
- Qualifications: Experience in product analytics, experimentation, and strong SQL skills required.
The predicted salary is between 60000 - 80000 £ 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 analyse experiments with statistical precision, standardise how experiments run across squads, and help the organisation 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 behaviour into insight: Run deep‑diving 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 organisation 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.
- Role‑Specific Assessment: A live session focused on the core technical or functional skills required for the role. This is your chance to show us how you tackle real‑world challenges.
- 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.
Senior Data Scientist - Stealth AI in City of Westminster employer: jobr.pro
At jobr.pro, we pride ourselves on being an excellent employer by fostering a flexible and culturally diverse work environment in Exeter. Our commitment to personal development ensures that employees have ample opportunities for growth while enjoying attractive benefits, making it a rewarding place to advance your career in the transport infrastructure sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist - Stealth AI in City of Westminster
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like jobr.pro!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Scientist - Stealth AI at jobr.pro.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like jobr.pro.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Scientist - Stealth AI at jobr.pro, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Scientist - Stealth AI in City of Westminster
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at jobr.pro, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at jobr.pro. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at jobr.pro
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at jobr.pro!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.