At a Glance
- Tasks: Lead a talented team to drive data engineering and machine learning innovations.
- Company: Fast-scaling tech platform in London with a focus on AI-driven products.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Dynamic environment that values collaboration and agile execution.
- Why this job: Make a significant impact by shaping the future of intelligent platforms.
- Qualifications: Proven leadership in data engineering and machine learning with strong technical skills.
The predicted salary is between 72000 - 88000 £ per year.
A fast-scaling, high-growth technology platform in London is looking for an experienced Head of Data Engineering & Machine Learning to drive the next evolution of their intelligent platform.
In this high-impact executive role, you will take full ownership of the technical vision, data architecture, and model estate. You’ll sit at the intersection of deep technical execution and commercial strategy, leading a talented group of engineers while partnering directly with executive leadership to convert business ambition into scalable, AI-driven products.
Key Responsibilities
- Leadership & Team Growth: Mentor, scale, and inspire a world-class team of data and ML engineers, instilling high standards for software execution, operational excellence, and continuous growth.
- Technical Strategy & Architecture: Define and execute the long-term vision for enterprise data infrastructure and machine learning systems to ensure long-term scalability.
- Strategic Roadmap Delivery: Own technical execution timelines, balancing speed-to-market with architectural rigor through smart technical trade-offs.
- Cross-Functional Partnership: Collaborate with Product, Commercial, and Go-To-Market leads to align engineering milestones with top-line business growth and revenue drivers.
- Hands-on Technical Bar: Champion AI-assisted development practices across the team while remaining close enough to the code to guide technical decision-making.
What We Are Looking For
- Proven Leadership: Demonstrated track record of building and managing high-performing engineering teams in data engineering, platform, or machine learning spaces.
- Track Record of Impact: Hands-on experience shipping enterprise-grade data platforms and machine learning solutions that deliver tangible commercial outcomes.
- Technical Credibility: Strong foundational depth in modern data architecture and ML deployment, with a passion for getting into the engineering details when necessary.
- Executive Communication: Exceptional ability to translate complex technical concepts into clear, value-driven narratives for C-suite and non-technical stakeholders.
- Commercial Acumen: Comfortable engaging on business drivers such as growth, monetization, and competitive differentiation.
- Agile Mindset: Thrives in dynamic, fast-paced environments where collaboration and adaptable execution are paramount.
Head of Data Engineering & Machine Learning in London employer: Retelligence
At Retelligence, we pride ourselves on fostering a dynamic work culture that encourages innovation and collaboration. As a Senior AI Infrastructure Engineer, you'll not only tackle complex challenges but also have access to continuous learning opportunities and career growth, all while making a tangible impact on our customers. Located in a vibrant tech hub, we offer a supportive environment where your contributions are valued and recognised.
StudySmarter Expert Advice🤫
We think this is how you could land Head of Data Engineering & Machine Learning in London
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Retelligence.
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We think you need these skills to ace Head of Data Engineering & Machine Learning in London
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Retelligence, 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 Retelligence. 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 Retelligence
✨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!
✨Showcase Your Projects
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 Retelligence!
✨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.
