Europe Arbeitnow ·
full-timeJunior Data Scientist
Livescore9 · London
Livescore9 operates as part of the LiveScore Group, which runs the LiveScore, LiveScore Bet and Virgin Bet brands in the sports media and sports betting space. The Junior Data Scientist will join the Marketing Analytics team and work on the end‑to‑end Marketing Mix Modelling (MMM) pipeline. Day‑to‑day tasks include gathering, cleaning and structuring time‑series marketing data, building and refining statistical models to measure channel ROI, and calibrating those outputs with incrementality test results such as GeoX experiments. The role also involves translating model insights into budget‑scenario simulations, using SQL to explore first‑party user data and track key KPIs, collaborating with data engineering to automate ingestion pipelines, and presenting complex econometric or machine‑learning findings in clear, visual recommendations for marketing leads and senior leadership. The position is hybrid, requiring three days a week in the Soho, London office. It suits candidates with a quantitative degree or experience, proficiency in Python (or R) and SQL, and an interest in modern MMM frameworks, econometrics, time‑series analysis and stakeholder communication.
Soho, London Hybrid working: 3 days in the office Tues - Thurs The Role We are looking for a brilliant and motivated Junior Data Scientist to join our Marketing Analytics team. In this role, you will help us measure, optimize, and supercharge our marketing investments across our core brands, with a strong focus on our mathematical and econometric modelling frameworks. You will have a unique opportunity to develop a dual profile: a rigorous data scientist who can manipulate complex datasets and build advanced models, and a strategic partner who translates those insights into clear growth strategies. You will step into a key position, taking hands-on ownership of our Marketing Mix Modelling (MMM) pipeline and helping us bridge the gap between statistical modelling, incrementality testing, and real-world multi-million-pound budget decisions. At LiveScore Group, we’re the proud home of three of the most exciting brands in the sports and gaming world: LiveScore, LiveScore Bet and Virgin Bet. A fully owned and operated ecosystem that converges the two worlds of sports media and sports betting. We’re proud of the high ratings for our commitment to excellence and fueling fan’s passion for sport driving us to the top. We don’t just lead; we innovate. Our cutting-edge products and immersive experiences set the standard, but it’s our people who truly make the difference. Every day, our team embody our values: adaptability, teamwork, a fan-driven approach, and an ever-curious mindset that fuels our ambition. As we scale and continue to create a culture that allows all employees to thrive, we know we need the most talented people with diverse backgrounds, perspectives and skills. If you’re good at what you do, come and join us. The more inclusive we are, the more amazing experiences we can create for our users. We know that job descriptions can sometimes seem daunting and you might not feel you tick every box. But, if you’re passionate about the role and have relevant experience, we want to hear from you! Key Responsibilities Hands-on Marketing Mix Modelling (MMM): Play a key role in our end-to-end MMM pipeline. You will be responsible for gathering, cleaning, and structuring time-series marketing data (spend, impressions, external factors) and building/refining statistical models to measure the ROI of our channels. Model Calibration & Triangulation: Help calibrate our MMM outputs using results from incrementality testing. You will actively use ground-truth experimental data (e.g., GeoX tests, attribution model). Budget Scenario Planning: Translate model outputs into actionable simulation tools and optimization scenarios. You will help stakeholders answer critical "what-if" questions regarding budget reallocations and product splits. User Data & Performance Analytics: Use SQL to deep-dive into first-party user data and tracking key KPIs. Data Quality & Pipeline Ownership: Collaborate with our Data Engineering teams to automate data ingestion pipelines, ensuring high-quality, model-ready inputs from ad-platforms, attribution tools, and internal databases. Stakeholder Communication: Translate complex econometric, Bayesian, or machine learning concepts into clear, commercial, and highly visual recommendations for marketing team leads and senior leadership. Skills, Knowledge and Experience Proven experience or a degree in a highly quantitative field (e.g., Econometrics, Statistics, Mathematics, Data Science, Economics, or Engineering). Python (or R) proficiency: Solid programming foundations for data manipulation (pandas, numpy), statistical modeling, and machine learning (we primarily use Python). Strong SQL skills: Comfortable writing efficient, structured queries to extract and aggregate massive datasets from relational databases. MMM Frameworks: Exposure to or strong interest in modern open-source MMM libraries (e.g., Meta's Robyn, Google's Meridian, or PyMC/Bayesian workflows). Solid foundation in econometrics, time-series analysis, and regression modeling (OLS, Ridge/Lasso, Bayesian regression). Good understanding of testing and experimentation methodologies (A
| Role | Junior Data Scientist |
|---|---|
| Company | Livescore9 |
| Location | London |
| Compensation | Not disclosed |
| Deadline | Rolling |
Typical process for this type of role
A general guide — the exact steps for this specific listing may vary; check the original posting for details.
- 1ApplicationSubmit your resume through the apply link.
- 2ScreeningRecruiter reviews your background against the role.
- 3AssessmentA technical test, assignment, or coding round, depending on the role.
- 4Interview(s)One or more rounds with the hiring team.
- 5OfferOffer letter with compensation and start date.
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