At a Glance
- Tasks: Enhance Python tools and automate workflows for impactful marketing insights.
- Company: Leading independent media agency in Central London with a hybrid work model.
- Benefits: Competitive salary up to £45,000 and opportunities for professional growth.
- Other info: Mentorship opportunities and a collaborative environment await you.
- Why this job: Join a dynamic team and make a real difference in data-driven marketing.
- Qualifications: Strong Python and SQL skills, plus a degree in a related field.
Data Science Engineer – MMM/Econometrics (Central London, Hybrid)
Salary: Up to £45,000 (depending on experience) – Reference J13129
We are a leading independent media agency looking for a Data Science Engineer to sit at the intersection of data science and engineering, supporting the marketing effectiveness team in delivering high‑impact, data‑driven insights.
Responsibilities
- Maintain and enhance core Python modelling tools for Marketing Effectiveness.
- Migrate manual workflows into automated production systems.
- Develop in‑house tools that improve our MMM and econometric capabilities.
- Diagnose and resolve complex technical issues across production systems.
- Work closely with analysts and stakeholders to solve domain‑specific challenges.
- Ensure accuracy and configuration of tools used in client delivery.
- Produce clear technical documentation and promote best practices.
- Mentor junior engineers and contribute to peer code reviews.
Qualifications
- Strong Python engineering skills (clean, modular, production‑ready code).
- Experience in data science, including ML/statistical modelling for MMM and econometrics.
- Strong SQL for data extraction and analysis.
- Solid understanding of software engineering fundamentals (Git, agile workflows).
- Ability to communicate complex ideas clearly to technical and non‑technical audiences.
- Degree in Computer Science, Data Science, or a related field.
If this sounds like the role for you, please apply today!
Data Science Engineer - MMM/Econometrics employer: Datatech Analytics
As a leading independent media agency based in Central London, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to thrive. With a strong focus on professional development, we offer numerous growth opportunities, mentorship from experienced engineers, and the chance to work on impactful projects that drive marketing effectiveness. Our hybrid working model ensures a healthy work-life balance, making us an excellent employer for those seeking meaningful and rewarding careers in data science.
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We think this is how you could land Data Science Engineer - MMM/Econometrics
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We think you need these skills to ace Data Science Engineer - MMM/Econometrics
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!
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Craft a Tailored Cover Letter:For a full-time role at Datatech Analytics, 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 Datatech Analytics. 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 Datatech Analytics
✨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
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 Datatech Analytics!
✨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.
