At a Glance
- Tasks: Join a leading media agency as a Data Science Engineer, enhancing marketing effectiveness through data-driven insights.
- Company: One of the UK's top independent media agencies with a focus on innovation.
- Benefits: Competitive salary up to £45,000, hybrid work model, and referral bonuses.
- Other info: Dynamic team environment with opportunities for mentorship and career growth.
- Why this job: Make a real impact by automating workflows and developing tools for major brands and charities.
- Qualifications: Strong Python and SQL skills, experience in data science, and a degree in a related field.
The predicted salary is between 45000 - 45000 £ per year.
Amazing opportunity to join one of the UK's leading independent media agencies as a Data Science Engineer. A pivotal technical role sitting at the intersection of data science and engineering, supporting the marketing effectiveness team in delivering high impact, data driven insights.
Working for an IPA Effectiveness accredited agency, across multiple leading brands and charities helping to transition manual workflows into scalable, automated, production ready systems, building innovative tools which strengthen the marketing mix modelling and econometrics capabilities.
What you'll do:
- 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
You'll need to have:
- 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 related field
If this sounds like the role for you then please apply today!
Data Science Engineer - MMM/Econometrics employer: Datatech Analytics
Join a dynamic and innovative independent media agency in Central London as a Data Science Engineer, where you'll be at the forefront of transforming marketing effectiveness through data-driven insights. With a strong emphasis on employee growth, you will have opportunities to mentor junior engineers and contribute to peer code reviews, all within a collaborative and supportive work culture that values creativity and technical excellence. Enjoy a competitive salary, hybrid working arrangements, and the chance to work with leading brands and charities, making a meaningful impact in the industry.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Engineer - MMM/Econometrics
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals 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 Python projects, data science models, or any relevant work. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios related to MMM and econometrics. Mock interviews with friends or mentors can help you feel more confident and ready to impress.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are eager to join our team!
We think you need these skills to ace Data Science Engineer - MMM/Econometrics
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Science Engineer role. Highlight your Python skills, data science experience, and any relevant projects that showcase your ability to work with marketing effectiveness tools.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your skills align with our needs. Don’t forget to mention specific experiences that relate to MMM and econometrics.
Showcase Your Technical Skills:When filling out your application, be sure to highlight your technical skills, especially in Python and SQL. We want to see examples of clean, modular code and any projects where you've automated workflows or solved complex issues.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it’s super easy!
How to prepare for a job interview at Datatech Analytics
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially focusing on writing clean, modular, and production-ready code. Be prepared to discuss your past projects and how you've maintained or enhanced Python modelling tools for marketing effectiveness.
✨Showcase Your Data Science Experience
Be ready to talk about your experience with ML and statistical modelling, particularly in the context of marketing mix modelling (MMM) and econometrics. Prepare examples that demonstrate how you've applied these skills to solve real-world problems.
✨Communicate Clearly
Since you'll be working closely with analysts and stakeholders, practice explaining complex technical concepts in simple terms. This will show your ability to bridge the gap between technical and non-technical audiences, which is crucial for this role.
✨Prepare for Technical Challenges
Expect to face some technical questions or challenges during the interview. Brush up on your SQL skills for data extraction and analysis, and be ready to discuss your understanding of software engineering fundamentals like Git and agile workflows.
