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 opportunities for professional growth.
- Other info: Mentorship opportunities and a vibrant team culture await you!
- Why this job: Make a real impact by automating workflows and developing tools that shape marketing strategies.
- Qualifications: Strong Python 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
Join one of the UK's leading independent media agencies as a Data Science Engineer, where you'll thrive in a dynamic and collaborative work culture that values innovation and professional growth. With a focus on mentoring and skill development, this role offers the chance to work on impactful projects across renowned brands and charities, all while enjoying the vibrant atmosphere of Central London. Benefit from competitive remuneration, flexible hybrid working arrangements, and unique referral schemes that reward your contributions to the team.
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 potential colleagues 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 models, or any tools you've developed. This gives you a tangible way to demonstrate your expertise and makes you stand out in interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your SQL and Python skills. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and solve problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, if you refer a friend, you could snag some cool rewards while helping someone else land their dream job!
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 develop tools for marketing effectiveness.
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 background aligns with our mission at StudySmarter. Keep it concise but impactful!
Showcase Your Technical Skills:Don’t forget to mention your strong SQL skills and understanding of software engineering fundamentals. We love seeing examples of clean, modular code, so if you have a GitHub or portfolio, link it up!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to see your application and get you into the process quickly. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Datatech
✨Know Your Python Inside Out
As a Data Science Engineer, you'll need to showcase your strong Python skills. Brush up on writing clean, modular, and production-ready code. Be prepared to discuss specific projects where you've used Python for marketing effectiveness or econometrics.
✨Showcase Your Data Science Experience
Make sure to highlight your experience with ML and statistical modelling, especially in the context of marketing mix modelling (MMM). Prepare examples of how you've applied these techniques to solve real-world problems, as this will resonate well with the interviewers.
✨Communicate Clearly
You’ll be working with both technical and non-technical stakeholders, so practice explaining complex ideas in simple terms. Think of examples where you’ve had to bridge the gap between data science and business needs, and be ready to share those stories.
✨Prepare for Technical Challenges
Expect to face some technical questions or challenges during the interview. Brush up on SQL for data extraction and analysis, and be ready to discuss your understanding of software engineering fundamentals like Git and agile workflows. Practising coding problems can also help!
