At a Glance
- Tasks: Analyse data to drive marketing decisions and create actionable insights.
- Company: Fast-growing B2B data analytics startup with a collaborative culture.
- Benefits: Competitive salary, equity, bonuses, and growth opportunities.
- Other info: Dynamic environment with ownership and autonomy in your role.
- Why this job: Join a high-impact team and make a real difference in marketing strategies.
- Qualifications: 2-4 years in analytics, strong SQL and Python skills, and experience in econometric modelling.
The predicted salary is between 50000 - 60000 £ per year.
Location: London (Hybrid - Chancery Lane Office)
Employment type: full time
Seniority: mid/senior
About Day1Data: Day1Data is a fast-growing B2B data analytics startup helping marketing and finance teams measure incrementality & make smarter marketing decisions. From marketing mix modelling to forecasting and data infrastructure, we help companies know what drives true growth. We work with leading global brands and are scaling rapidly - this is a great time to join a small, high-impact team.
Role overview: We are seeking a Marketing Scientist to join our team. This role will focus on experimentation, econometric modelling and the creation of actionable marketing insights. You will play a pivotal role in analysing customer acquisition and retention performance, designing measurement frameworks and building predictive models that influence commercial and strategic decisions.
- Experimentation & Causal Inference: Design, execute, and analyse experiments including geo-testing, A/B and multivariate testing. Use causal inference methods (e.g. synthetic control, difference-in-differences) to measure the incremental impact of marketing initiatives.
- Marketing Mix Modelling (MMM) & Econometrics: Develop and maintain econometric models to evaluate marketing effectiveness and optimise investment allocation. Leverage multiple modelling techniques: Bayesian / Frequentist. Contribute to long-term planning through investment forecasting and budget optimisation.
- Acquisition & Retention Analytics: Analyse performance across acquisition channels and customer cohorts, identifying key drivers of customer behaviour and retention. Track and optimise KPIs such as CAC, LTV, churn, and conversion across the lifecycle.
- Predictive Modelling & Segmentation: Build and deploy models for churn prediction, CLTV forecasting, and customer segmentation. Use model outputs to inform lookalike targeting, personalisation strategies, and performance marketing.
- Attribution & Measurement: Develop multi-touch attribution models to assess marketing effectiveness across channels. Model expected outcomes of marketing initiatives and quantify their commercial impact.
- Stakeholder Collaboration: Partner with marketing, finance, data science, and product teams to align on business objectives and translate analytical insights into action. Present findings in a clear, compelling way to both technical and non-technical stakeholders.
What you’ll need:
- Proven experience (2–4 years) in an analytics or data science role.
- Strong command of experimentation design and analysis (especially geo-based and incrementality testing).
- Experience in building MMM or econometric models.
- Proficiency in SQL and Python.
- Experience with attribution modelling and measurement frameworks.
- Familiarity with causal inference techniques (e.g., Bayesian structural time series, CausalImpact, etc.).
- Exposure to cloud-based analytics environments (e.g., BigQuery, Snowflake).
What we offer:
- Competitive salary
- Equity
- Bonus
- Growth opportunities - A chance to build your career at a fast-paced data business, working on AI projects
- Ownership and autonomy - Real ownership and an opportunity to make a significant impact on our journey
- Collaborative culture - A fast-paced, energetic environment where big ideas are encouraged
Data Analyst - Marketing in London employer: Day1Data
At Day1Data, we pride ourselves on being an excellent employer by fostering a collaborative culture that encourages innovation and big ideas. Located in the vibrant Chancery Lane area of London, our hybrid work model offers flexibility while providing opportunities for professional growth in a fast-paced B2B data analytics startup. Join us to make a significant impact on our journey and enjoy competitive salaries, equity, and the chance to work on exciting AI projects.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst - Marketing in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Day1Data!
✨Show Off Your Projects
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Day1Data.
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We think you need these skills to ace Data Analyst - Marketing in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Day1Data, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Day1Data. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Day1Data
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Day1Data!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
