At a Glance
- Tasks: Build analytics foundations to drive business insights and product decisions.
- Company: Fast-growing tech company revolutionising investment research with LLM-powered tools.
- Benefits: Competitive pay, equity, private health insurance, gym membership, and exciting team offsites.
- Other info: Dynamic environment with real ownership and massive growth potential.
- Why this job: Be the first data hire and shape the future of our analytics strategy.
- Qualifications: Strong data analytics skills, experience with SQL, Python, and product analytics platforms.
The predicted salary is between 60000 - 80000 £ per year.
About Junior
We're building cutting-edge LLM-powered tools that supercharge investment research for the world's most demanding deal teams. Our clients include several of the top 10 global private equity firms, Big 4 professional services firms, and leading consulting practices: organisations responsible for deploying billions of dollars annually. We're a profitable, bootstrapped company with a growing team of ~45 people based in London and New York. We 10x'd our revenue in 2025 and are on track to grow 2-3x this year. Junior saves clients an average of 10 hours per week, and we're expanding fast into new verticals including investment banking, hedge funds, and research firms.
Role Description
As our first dedicated data hire, you’ll build the analytics foundation that helps us understand what’s really driving the business - what users love, what makes customers retain, where deals are won/lost, and where we should focus next. This is a foundational role with massive visibility and ownership.
- Sample set of projects
- Feature adoption & engagement analysis: identify which features drive retention and which are dead weight - slice by firm type, user role, and tenure to give our Product team clear prioritisation signals.
- Churn & health scoring: build a customer health model that scores accounts by risk using product usage signals (logins, feature depth, search volume) and flags at-risk accounts to Customer Success before they churn.
- CRM data quality & enrichment: audit and clean our CRM data, build pipelines to keep it in sync with product usage, and ensure our Sales team always has accurate, up-to-date context on every account.
- Sales funnel analysis: map our full acquisition funnel from first touch to closed-won, identify where deals are stalling, and surface the product usage patterns that predict conversion.
- Executive reporting: build a weekly data digest for leadership covering revenue, usage, pipeline health and key anomalies - replacing ad hoc spreadsheets with a reliable, automated view of the business.
About You
We’re looking for a data scientist who loves getting into the detail of how a product is actually being used and translating that into decisions:
- Based in LDN, and excited to be in office 5 days / week
- Strong data analytics skillset
- SQL
- Python for data wrangling, analysis and visualization (pandas, matplotlib / plotly etc)
- BI or dashboarding tool - Metabase, Looker, Tableau, or similar
- AI-forward: experience vibe coding and using AI tools
- Relevant prior experience
- Has worked with product analytics platforms like Amplitude, Mixpanel, or equivalent - comfortable with event-level data and funnel analysis
- Experience working directly with CRM or similar data
- Bonus points for experience in B2B SaaS, fintech, or enterprise software where usage data is complex and customer segments vary widely
- Strong communicator who can tell a clear story with data - our commercial stakeholders are smart but non‑technical, and they’ll rely on you to make the numbers make sense
- Self‑directed and comfortable with ambiguity — there’s no existing data team to hand off to; you’ll define the questions as often as you answer them.
Why This Role
Real ownership: You’ll be the first data hire. You’re not inheriting legacy dashboards or maintaining old reports — you’re building the foundation from scratch. Direct impact: Your work will influence product roadmap, sales strategy, customer success, and executive decision‑making. Massive upside: We’re already at $15M+ ARR and scaling quickly. The systems you build now will support the next 10x of growth. Strong business fundamentals: Profitable, bootstrapped, and growing fast — no investor theatre, no fluff, just real traction.
Benefits
All the usual benefits (competitive pay, equity, etc) + Private health insurance Gym membership (Third Space) Dinner in office Frequent team offsites (Crete, Upstate NY, Cancun)
If you're excited about the opportunity to drive innovation at Junior, we'd love to hear from you! We can't wait to meet you!
Data Scientist - Commercial Analytics employer: Junior AI
At Junior, we pride ourselves on being an innovative employer that fosters a dynamic work culture in the heart of London. As a Data Scientist, you'll enjoy unparalleled ownership and visibility in your role, contributing directly to our rapid growth while benefiting from competitive pay, private health insurance, and exciting team offsites. Join us to be part of a collaborative environment where your insights will shape the future of investment research and drive meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Commercial Analytics
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Junior. A personal introduction can make all the difference when it comes to landing that interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving SQL, Python, or any analytics tools. This will give you an edge and demonstrate your hands-on experience to the hiring team.
✨Tip Number 3
Prepare for the interview by diving deep into Junior's products and understanding their analytics needs. Be ready to discuss how your insights can drive product decisions and improve customer retention.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of our growing team.
We think you need these skills to ace Data Scientist - Commercial Analytics
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Data Scientist role. Highlight your data analytics skills, experience with SQL and Python, and any relevant projects you've worked on. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you're excited about this role at Junior. Share your passion for data and how you can help us build the analytics foundation. Be genuine and let your personality shine through!
Showcase Your Projects:If you've worked on any relevant projects, especially those involving product analytics or CRM data, make sure to mention them. We love seeing real examples of your work and how you've used data to drive decisions.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen to join our team!
How to prepare for a job interview at Junior AI
✨Know Your Data Tools
Make sure you’re well-versed in SQL and Python, as these are crucial for the role. Brush up on your data wrangling and visualisation skills using libraries like pandas and matplotlib. Being able to demonstrate your proficiency with these tools will show that you're ready to hit the ground running.
✨Understand the Business Impact
Familiarise yourself with how data analytics drives business decisions, especially in a B2B SaaS context. Be prepared to discuss how your previous work has influenced product roadmaps or sales strategies. This will help you connect your technical skills to real-world outcomes, which is key for this role.
✨Prepare for Scenario Questions
Expect questions that ask you to analyse hypothetical data scenarios or past experiences. Think about how you would approach feature adoption analysis or churn scoring. Practising these scenarios will help you articulate your thought process clearly during the interview.
✨Communicate Clearly
Since you'll be working with non-technical stakeholders, practice explaining complex data concepts in simple terms. Prepare examples of how you've successfully communicated insights in the past. This will demonstrate your ability to bridge the gap between data and decision-making.
