At a Glance
- Tasks: Use causal inference to analyse customer behaviour and drive strategic decisions.
- Company: Join a global consumer tech company building a new Data Science team.
- Benefits: Competitive salary, bonus, and largely remote work with occasional office visits.
- Other info: Opportunity for career growth in a collaborative and innovative team.
- Why this job: Shape high-impact strategies and make a real difference in a dynamic environment.
- Qualifications: Experience in causal inference and strong statistical foundations required.
The predicted salary is between 70000 - 90000 £ per year.
Can you distinguish genuine incremental growth from value simply shifting elsewhere? Do you use causal inference to explain why customer behaviour changes, rather than just predict what happens next? Would you like to help build a brand-new Data Science team focused on high-impact product and commercial strategy?
A global consumer technology business is building a new User Value Strategy team and hiring a Senior Data Scientist to shape its approach to experimentation, causal reasoning and strategic decision-making. This is a classical Data Science and econometrics role rather than ML Engineering, focused on understanding the true impact of product and commercial initiatives across a large consumer ecosystem.
Responsibilities- Apply causal inference and counterfactual methods to understand the true impact of product and commercial changes
- Analyse incrementality, cannibalisation and value decomposition across the ecosystem
- Work on experimentation, A/B testing and off-policy evaluation
- Develop simulation and evaluation frameworks to estimate outcomes before expensive experiments
- Translate complex findings into clear strategic recommendations
- Strong experience in causal inference, experimentation or econometrics
- Depth in areas such as counterfactuals, cannibalisation, off-policy evaluation or value decomposition
- Strong statistical foundations and a research-oriented approach
- Ability to explain complex methodologies clearly to commercial and product stakeholders
- Master's or PhD preferred, ideally in Economics, Econometrics, Statistics or a related quantitative field
- Level: Senior Data Scientist, open to Mid-level
- Salary: Up to £124,000 base + bonus
- Location: London
- Working model: Largely remote. London office visit once every 6 weeks
Interested? Apply below.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Causal Inference & Experimentation in England
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We think you need these skills to ace Data Scientist - Causal Inference & Experimentation in England
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 Harnham, 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 Harnham. 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 Harnham
✨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!
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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
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✨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.
