At a Glance
- Tasks: Drive product innovation by transforming customer insights into actionable data.
- Company: Join Mention Me, a leader in authentic marketing solutions.
- Benefits: Enjoy hybrid working, private medical insurance, and 25 days annual leave.
- Why this job: Make a real impact in a fast-paced, innovative environment with cutting-edge technology.
- Qualifications: 4+ years in data science, strong Python and SQL skills, and a passion for continuous learning.
- Other info: Collaborative culture with regular social events and excellent career growth opportunities.
The predicted salary is between 48000 - 72000 £ per year.
About Mention Me: Mention Me amplifies the authentic human voice in a world of AI marketing noise to drive profitable brand growth. We help brands identify true promoters, activate authentic recommendations and UGC, and align teams around a single source of Voice of Customer insights so real brand love compounds into performance across channels.
The opportunity: Become one of the top contributors to bring the new product vision live. Work end to end across metric design, data and modeling, experimentation, and product integration.
What you'll do:
- Build components of new products that turn real customer signals into timely actions and measurable outcomes allowing customers to amplify consumer voice for LLM visibility advantage. Partner across Product, Engineering, CS, and Commercial to make the human signal visible, actionable, and compounding in the product.
- Establish experimentation and measurement foundations: design how we test, learn, and prove impact; embed sound statistical practice; and turn results into simple, trusted narratives that guide product and commercial decisions.
- Productionize and scale thoughtfully: ship durable data and model workflows in collaboration with the engineering team, ensure quality and monitoring, and document decisions so the system is reliable, explainable, and easy to evolve.
What you'll bring:
- Track record, typically 4+ years, in applied data science for product or marketing in consumer or SaaS.
- Continuous learning mindset: you stay current with generative AI advances, prototype with new models and frameworks, evaluate them critically, and translate useful innovations into practical product improvements. You share learnings and raise the bar for the team.
- Hands-on ML skills: feature engineering, propensity or uplift modeling, model evaluation, monitoring.
- Strong Python and SQL with the ability to move from notebooks to production code.
- Practical data engineering instincts: event schemas, batch jobs, orchestration, data quality guardrails.
- Clear communication that translates complexity into actionable narratives for non-technical audiences.
- Bias for action and ownership in ambiguous, fast-moving environments.
Nice to have:
- LLM applications for agentic solutions.
- Graph modeling.
- Personalization: propensity/uplift modeling, bandits, causal inference.
- Libraries: scikit-learn, XGBoost, LightGBM, CatBoost, CausalML, Keras, DoWhy.
- Experience with dbt, Airflow, Looker or Metabase, AWS services such as S3 and Lambda.
- Experience in designing and implementing model/metric endpoints as part of a platform ecosystem with clear contracts and SLOs (e.g., FastAPI/Flask, OpenAPI), deploying via AWS Lambda/API Gateway or containers.
How we work:
- Hybrid with in-person collaboration at our Vauxhall HQ and flexibility for focused work.
- Cross-functional by default with close partnership across Product, Engineering, CS, and Commercial.
- Outcome-driven with small releases, fast validation, and scaling what works.
Benefits: Here are some of our favourite perks and benefits, but we have so many more:
- Hybrid working.
- Private medical insurance with Vitality, including enhanced mental wellbeing support, dental and vision policies and a range of lifestyle benefits and great incentives.
- Life insurance.
- Two Celebration Days; additional time off for you to celebrate religious days, cultural events, birthdays, anniversaries, or any other significant day that's important to you.
- Enhanced parental leave.
- 25 days annual leave (plus public holidays), increasing over your time as a Mentioneer.
- Regular social events, from chocolate-tasting and pottery-making to poker nights and picnics.
- Up-to-date tech you'll need (we love Macs).
Senior/Lead Data Scientist in London employer: Mention Me
Contact Detail:
Mention Me Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior/Lead Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects and experiments. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨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 love seeing candidates who are proactive!
We think you need these skills to ace Senior/Lead Data Scientist in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Senior/Lead Data Scientist role. Highlight your relevant experience in data science, especially in product or marketing, and show us how you can amplify the consumer voice with your skills.
Show Off Your Skills: We want to see your hands-on ML skills in action! Include specific examples of your work with Python, SQL, and any relevant libraries. Don’t forget to mention your experience with experimentation and measurement foundations – we love a good data story!
Keep It Clear and Concise: When writing your application, clarity is key. Use straightforward language to explain complex concepts, especially if they relate to your past projects. Remember, we’re looking for someone who can communicate effectively with both technical and non-technical audiences.
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 don’t miss out on any important updates about the hiring process. We can’t wait to hear from you!
How to prepare for a job interview at Mention Me
✨Know Your Data Science Stuff
Make sure you brush up on your data science skills, especially in Python and SQL. Be ready to discuss your hands-on experience with machine learning techniques like feature engineering and model evaluation. They’ll want to see how you can translate complex data into actionable insights.
✨Show Off Your Experimentation Skills
Prepare to talk about how you've designed experiments and measured their impact in previous roles. Mention any statistical practices you've embedded in your work and be ready to share narratives that simplify complex results for non-technical audiences.
✨Demonstrate Your Continuous Learning Mindset
Mention any recent advancements in generative AI that you've explored or implemented. They value a candidate who stays current with industry trends and can critically evaluate new models. Share examples of how you've translated these innovations into practical improvements.
✨Communicate Clearly and Confidently
Practice explaining your past projects and technical concepts in a way that's easy to understand. Clear communication is key, especially when discussing your work with cross-functional teams. Make sure you can convey your ideas confidently and concisely.