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For Companies At a Glance
- Tasks: Lead a data science team and drive impactful analytical projects for major brands.
- Company: High-growth performance marketing and technology business with a collaborative culture.
- Benefits: Competitive salary, hybrid working, and opportunities for professional growth.
- Other info: Mentorship opportunities and access to large-scale datasets.
- Why this job: Shape marketing strategies with data and make a real difference in the industry.
- Qualifications: Strong SQL skills and experience in experimentation methodologies.
The predicted salary is between 65000 - 65000 £ per year.
This is an exciting opportunity to join a high-growth organisation where data science directly shapes performance marketing strategy. You will lead a growing data science function, drive long-term analytical programmes, and play a key role in delivering meaningful commercial impact for well-known consumer brands.
The Company
They are a specialist performance marketing and technology business known for combining deep analytical expertise with innovative data products. With a rapidly expanding team and a strong track record of industry recognition, they partner with major consumer brands to solve complex measurement, forecasting, and modelling challenges. Their culture is collaborative, modern, and driven by delivering high-quality work that genuinely moves the needle for clients. As they scale, they are investing heavily in data science, experimentation, and advanced analytics.
The Role
As Lead Data Analyst, you will oversee a team of data scientists and work closely with senior stakeholders across analytics, data engineering, and technology. You will:
- Lead experimentation and measurement initiatives including incrementality testing, geo-based studies, brand lift approaches, and causal inference.
- Own advanced modelling projects such as MMM, LTV modelling, propensity scoring, and predictive forecasting.
- Guide long-term analytical roadmaps and ensure projects drive measurable commercial impact.
- Partner with high-profile clients, often with direct access to raw data, applying rigorous analytical thinking to real-world marketing challenges.
- Mentor and support a growing team of data scientists as they expand through the year.
Requirements
- Strong commercial experience with SQL.
- Deep knowledge of experimentation methodologies such as incrementality, causal inference, geo testing, or brand lift studies.
- Experience delivering impactful, long-term analytics or data science projects.
- Management or mentoring experience is desirable, but they are also open to strong individual contributors ready to step up.
- Exposure to attribution modelling is a bonus.
Benefits
- Hybrid working with one day per week in their London office.
- The opportunity to lead a growing data science function with genuine ownership and influence.
- Work with large-scale datasets from major consumer brands.
- A culture that invests in innovation, long-term thinking, and high-impact analytics.
How to Apply
If you are ready to take the next step in your data science career, apply today to find out more.
Lead Data Analyst Python SQL in London employer: Harnham - Data & Analytics Recruitment
Contact Detail:
Harnham - Data & Analytics Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Analyst Python SQL in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, especially those involving SQL and Python. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on key concepts related to experimentation methodologies and advanced modelling. Be ready to discuss how you've applied these in real-world scenarios, as this will resonate well with hiring managers.
✨Tip Number 4
Don't forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Lead Data Analyst Python SQL in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your experience with SQL and any relevant data science projects you've led. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data analytics and how you can contribute to our team. Be sure to mention any specific methodologies or projects that relate to the role.
Showcase Your Analytical Skills: In your application, don’t just list your skills—show us how you've used them in real-world scenarios. Whether it's through case studies or examples of past work, we love seeing how you’ve made an impact with data.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re genuinely interested in joining our team!
How to prepare for a job interview at Harnham - Data & Analytics Recruitment
✨Know Your Data Inside Out
Before the interview, make sure you’re well-versed in the data tools and methodologies mentioned in the job description. Brush up on your SQL skills and be ready to discuss specific projects where you've applied advanced modelling techniques like MMM or LTV modelling.
✨Showcase Your Leadership Skills
Even if you’re not applying for a management role, it’s important to demonstrate your ability to mentor and guide others. Prepare examples of how you’ve supported team members or led projects, especially in areas like experimentation and measurement initiatives.
✨Prepare for Technical Questions
Expect technical questions that dive deep into your knowledge of experimentation methodologies. Be ready to explain concepts like incrementality testing and causal inference clearly, and think of real-world applications to illustrate your understanding.
✨Align with Company Culture
Research the company’s culture and values. They emphasise collaboration and high-quality work, so be prepared to discuss how you’ve contributed to a team environment and delivered impactful results in previous roles. Show them you’re a great fit for their modern, innovative approach!