At a Glance
- Tasks: Drive product success through data analysis and strategic decision-making.
- Company: Join a dynamic team at Cleo, leading in product analytics.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborate with a talented team of 80 data professionals.
- Why this job: Make a real impact by turning insights into innovative products.
- Qualifications: 5+ years in quantitative analysis, strong SQL skills, and excellent communication.
The predicted salary is between 60000 - 80000 € per year.
We are looking for a self-starter, focused on results, with a demonstrated success in using analytics to drive the understanding, growth, and success of a product.
- 5+ years of experience doing quantitative analysis within a digital product environment.
- Experience conducting large scale A/B experiments and interpreting results to drive product and business decisions.
- Ability to define new product metrics from complex, unstructured data.
- Excellent SQL skills.
- Fluency in Python and its application in data analysis is a nice to have, but not essential.
- Knowledge of statistics (e.g. hypothesis testing, regressions).
- Strong communication skills, with the ability to work fluidly across technical and non-technical teams.
- Hands-on experience with BI tools (e.g. Looker, Mode, Tableau) and data workflow tools (dbt, Airflow).
- A bias for action and ownership—you’re excited to build from scratch, own it end-to-end, and deliver value fast.
As a Senior / Lead Data Scientist in Product Analytics you’ll be at the centre of strategic decision-making within your team. Working as part of a cross-functional squad alongside product managers, designers, and engineers, you’ll apply your expertise to drive the future of what we build at Cleo.
You will leverage rich user data and sophisticated analytical techniques to see your insights turned into real products. You’ll also sit within the wider data science function here at Cleo; a hotshot team of 80 Product Analysts, Analytics Engineers, and Machine Learning Engineers, with significant industry experience that are at the heart of everything we do at Cleo.
Conduct deep-dive analysis in your product domain to understand user behaviour. Work with Product, Machine Learning, Design, and Engineering team-members in your area to build an insight-driven product strategy that leads to high-impact outcomes. Influence the roadmap of your team through presentation of data-based recommendations.
Define how we quantitatively evaluate success, setting KPIs, designing tracking to measure what really matters. Conduct regular A/B tests and causal analyses to determine the impact of product changes on success metrics. Build models of user-segmentation, marketing attribution, customer lifetime value etc. Work with Analytic Engineering to prioritise data modelling needs in your area as well as directly contributing to our transformed data codebase.
Senior / Lead Data Scientist (Product Analytics) employer: Deepstreamtech
At Cleo, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Senior / Lead Data Scientist in Product Analytics, you will have the opportunity to work alongside a talented team of 80 professionals, driving impactful product decisions through data-driven insights. With a strong emphasis on employee growth, we offer continuous learning opportunities and the chance to influence our product roadmap, all while enjoying the vibrant atmosphere of our London office.
StudySmarter Expert Advice🤫
We think this is how you could land Senior / Lead Data Scientist (Product Analytics)
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for those interviews! Brush up on your SQL and Python skills, and be ready to discuss your past projects. We want to see how you’ve used analytics to drive product success, so have some solid examples up your sleeve.
✨Tip Number 3
Show off your analytical prowess! When you get the chance, present your insights clearly and confidently. We love candidates who can communicate complex data findings to both technical and non-technical teams.
✨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, we’re always on the lookout for self-starters who are excited to own their projects from start to finish.
We think you need these skills to ace Senior / Lead Data Scientist (Product Analytics)
Some tips for your application 🫡
Showcase Your Experience:Make sure to highlight your 5+ years of experience in quantitative analysis. We want to see how you've used analytics to drive product success, so share specific examples that demonstrate your impact.
Be Data-Driven:When discussing your skills, focus on your ability to conduct A/B tests and interpret results. We love data-driven decision-making, so include any relevant metrics or outcomes from your past projects.
Communicate Clearly:Strong communication skills are key! Make sure your application reflects your ability to work with both technical and non-technical teams. Use clear language and avoid jargon where possible to show us you can bridge the gap.
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 this exciting opportunity at StudySmarter!
How to prepare for a job interview at Deepstreamtech
✨Know Your Numbers
Make sure you brush up on your quantitative analysis skills. Be ready to discuss specific examples of how you've used data to drive product decisions in the past. Highlight any A/B tests you've conducted and the insights gained from them.
✨SQL Savvy
Since excellent SQL skills are a must, practice writing complex queries before the interview. Be prepared to explain your thought process when working with databases and how you've used SQL to extract meaningful insights from large datasets.
✨Communicate Clearly
Strong communication skills are key for this role. Think about how you can convey complex data findings to non-technical team members. Prepare to share examples of how you've successfully collaborated with cross-functional teams in the past.
✨Show Your Ownership Mindset
Demonstrate your bias for action and ownership by sharing instances where you've taken initiative in previous roles. Discuss projects where you built something from scratch and how you ensured it delivered value quickly.
