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- Tasks: Analyse customer behaviour and design experiments to drive measurable improvements.
- Company: Fast-growing Series A tech start-up with a high-velocity environment.
- Benefits: Strong equity upside, competitive benefits, and a culture of ownership.
- Why this job: Make an immediate impact on product decisions and customer experience.
- Qualifications: 5+ years in data analytics, strong SQL skills, and a commercial mindset.
- Other info: Collaborative atmosphere with opportunities for continuous improvement and career growth.
The predicted salary is between 36000 - 60000 £ per year.
This is a critical front-line analytics position inside a high-velocity, Series A tech start-up that is scaling fast and making decisions in real time. We’re looking for a Senior Data Analyst who thrives where the data is messy, the problems are ambiguous, and the impact is immediate.
You’ll sit embedded within cross-functional squads working directly on customer-facing outcomes. Your analysis won’t live in decks — it will shape product decisions, operational design, and commercial strategy. You’ll work with live, high-volume operational data and partner closely with product, engineering, and operations to understand requirements, run experiments and deliver impactful analysis and insights around customer experience, customer behaviour and engagement with the digital product.
This is a role for someone who enjoys ownership, pace, and accountability.
What You’ll Be Doing- Analysing customer behaviour across journeys, touchpoints, and decision moments
- Designing experiments to test hypotheses and drive measurable improvement (A/B testing)
- Building KPIs and dashboards that teams actually use
- Translating complex data into clear, commercial recommendations
- Working end-to-end on scoped analytics projects — from problem definition to delivery
This role is for you if you:
- Are comfortable operating in a high-expectation, fast-moving environment
- Care more about impact than elegance
- Can move from raw data → insight → decision without hand-holding
- Enjoy working closely with operators, engineers, and product leaders
- Take pride in ownership and follow-through
5+ years’ experience in data analytics
Strong SQL and experience with BI / visualisation tools
Sharp analytical instincts and first-principles thinking
Confidence communicating insights to technical and non-technical stakeholders
A commercial mindset — you understand why the business cares, not just what the data says
The Environment- High talent density, low bureaucracy
- In-person collaboration with people who move fast and think hard
- Strong equity upside and benefits
- A culture that rewards ownership, intensity, and continuous improvement
Lead Data Analyst employer: Omnis Partners
Contact Detail:
Omnis Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Analyst
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. The more you engage, the better your chances of landing that Lead Data Analyst role.
✨Tip Number 2
Showcase your skills in real-time! Consider working on personal projects or contributing to open-source initiatives. This not only sharpens your abilities but also gives you tangible examples to discuss during interviews.
✨Tip Number 3
Prepare for those interviews by practising common data analysis scenarios. Think about how you would approach messy data or ambiguous problems, just like you would in the role. We want to see your thought process!
✨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 fast-paced team.
We think you need these skills to ace Lead Data Analyst
Some tips for your application 🫡
Show Your Analytical Skills: When writing your application, make sure to highlight your analytical skills and experience. We want to see how you've tackled messy data and ambiguous problems in the past, so share specific examples that demonstrate your ability to turn raw data into actionable insights.
Tailor Your Application: Don’t just send a generic application! Tailor your CV and cover letter to reflect the job description. We’re looking for someone who understands our fast-paced environment and can show us how their experience aligns with our needs. Make it personal!
Be Clear and Concise: We appreciate clarity, so keep your writing straightforward and to the point. Avoid jargon unless it’s relevant, and focus on communicating your key achievements and skills effectively. Remember, we want to understand your impact quickly!
Apply Through Our Website: Make sure to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Omnis Partners
✨Know Your Data Inside Out
Before the interview, dive deep into your past projects and be ready to discuss specific data analyses you've conducted. Be prepared to explain how you turned messy data into actionable insights, as this role demands a strong grasp of customer behaviour and engagement.
✨Showcase Your Experimentation Skills
Since A/B testing is a key part of the job, come armed with examples of experiments you've designed and the outcomes they produced. Highlight your ability to test hypotheses and drive measurable improvements, as this will resonate well with the company's fast-paced environment.
✨Communicate Clearly and Confidently
Practice translating complex data findings into simple, commercial recommendations. You’ll need to communicate effectively with both technical and non-technical stakeholders, so think about how you can make your insights relatable and impactful.
✨Emphasise Ownership and Accountability
This role is all about taking ownership, so be ready to share instances where you've led projects from start to finish. Discuss how you’ve navigated ambiguity and made decisions that had a direct impact on customer experience or product strategy.
