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- Tasks: Join our Data Science team to develop ML models and pipelines for marketing solutions.
- Company: RAPP is a leading data-centric marketing agency under Omnicom, known for innovation.
- Benefits: Enjoy flexible working, mental health support, and opportunities for learning and development.
- Why this job: Be part of a dynamic team reinventing marketing with cutting-edge AI technology.
- Qualifications: Hands-on experience with ML models, Python, SQL, and cloud platforms required.
- Other info: We value diversity and offer a swift recruitment process with support throughout.
The predicted salary is between 30000 - 50000 ÂŁ per year.
We are looking for an ML Engineer to join our world-class Data Science team of around 8 data scientists led by George Cushen. As a business, we’ve won some of the biggest pitches in each category, such as Virgin Media 02, KFC, and Mercedes. Our clients say that we’re “reinventing the future of marketing”, applying the latest developments at the rapidly growing intersection of AI and marketing. We’re part of Omnicom, the global leader in marketing communications, and more specifically, we’re the data-centric arm of the Omnicom Precision Marketing Group (OPMG).
What You'll Focus On
- Leading the development of end-to-end pipelines for training, evaluating and deploying ML models to solve marketing problems
- Applying MLOps to operationalise ML models for clients’ marketing campaigns
- Supporting data scientists to build predictive models to improve media performance, customer experiences, revenue, and other outcomes across sectors like retail, telecoms, banking, and fast-food
- Developing performant data pipelines for AI model workflows
- Building lean Python web apps for self-service frameworks
- Transforming technology and processes with best practices
- Documenting projects for reproducibility and scaling
- Collaborating with data scientists and clients to identify ML opportunities
- Working with multiple teams in an agile environment
Who We’re Looking For
If you’re the right candidate, you likely:
- Are pragmatic and outcome-focused
- Think scientifically, validate assumptions, seek evidence
- Have hands-on experience with machine learning models
- Proficient with Python, SQL, Bash, HTML/CSS/JS, and Excel; familiar with Jupyter, Pandas, SciKit, PyTorch, CI/CD, Git
- Understand probability and statistics
- Experienced with containerisation (Docker, Kubernetes)
- Knowledge of cloud architecture, API design, security, deployment
- Hands-on with at least one major cloud platform
- Data visualization skills with Plotly and Matplotlib
- Creative problem solver with attention to detail
- Excellent communication skills
- Comfortable in a dynamic, high-growth environment
Preferred Qualifications
- MS or Ph.D. in relevant fields
- Understanding of marketing ecosystem and measurement frameworks
- Experience with data pipelines from sources like RedShift, SQLServer, Salesforce, Adobe Analytics
- Experience with AWS, Citrix, Databricks, Airflow, PySpark, web scraping, A/B testing, MLFlow, Dash, FastAPI, NLP, Computer Vision, GenAI, feature engineering
Key attributes
- Attention to detail, curiosity, proactivity
- Strong communication skills
About RAPP
We foster an inclusive workplace valuing diversity and individual differences. We support flexible working, learning and development, and diversity initiatives like The Neighbourhood. We prioritize wellbeing with coaching, mental health support, and family-friendly policies.
Recruitment process
We aim for a swift, personalized recruitment process with 2-3 stages. Our team is available to answer questions throughout. We are RAPP, and we look forward to meeting you!
ML Engineer employer: RAPP
Contact Detail:
RAPP Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in AI and marketing. Since we're at the intersection of these fields, showcasing your knowledge about how ML can transform marketing strategies will set you apart.
✨Tip Number 2
Engage with our Data Science team on platforms like LinkedIn. Commenting on their posts or sharing relevant articles can help you get noticed and demonstrate your genuine interest in our work.
✨Tip Number 3
Prepare to discuss specific projects where you've applied MLOps or built data pipelines. Being able to articulate your hands-on experience will show that you're not just familiar with the concepts but have practical skills to back them up.
✨Tip Number 4
Brush up on your communication skills. As collaboration is key in our agile environment, being able to clearly explain complex ML concepts to non-technical stakeholders will be a huge advantage.
We think you need these skills to ace ML Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the ML Engineer role. Focus on your hands-on experience with machine learning models, Python, SQL, and any cloud platforms you've worked with.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and marketing. Mention specific projects or experiences that demonstrate your problem-solving skills and ability to work in a dynamic environment.
Highlight Relevant Projects: Include details about any projects where you've developed end-to-end ML pipelines or worked with data visualisation tools like Plotly and Matplotlib. This will show your practical experience and understanding of the role.
Showcase Communication Skills: Since excellent communication is key for this role, consider including examples of how you've effectively collaborated with teams or clients in previous positions. This can set you apart from other candidates.
How to prepare for a job interview at RAPP
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with machine learning models and the technologies mentioned in the job description. Highlight your proficiency in Python, SQL, and any relevant frameworks like PyTorch or SciKit.
✨Demonstrate Problem-Solving Abilities
Expect to face scenario-based questions that assess your creative problem-solving skills. Use examples from your past experiences where you successfully tackled complex challenges, especially in a marketing context.
✨Communicate Clearly and Effectively
Strong communication skills are essential for this role. Practice explaining technical concepts in simple terms, as you may need to collaborate with non-technical stakeholders. Be ready to discuss how you would document projects for reproducibility.
✨Understand the Marketing Ecosystem
Familiarise yourself with the marketing ecosystem and measurement frameworks. Be prepared to discuss how machine learning can enhance marketing strategies and improve outcomes for clients across various sectors.
