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- Tasks: Lead a team of data scientists and drive machine learning engineering initiatives.
- Company: High-growth business in the UK with a focus on innovation.
- Benefits: Competitive salary of £115K - £125K plus bonus.
- Why this job: Shape the future of data strategy and make a significant impact.
- Qualifications: Proven leadership in data science and expertise in ML model deployment.
- Other info: Hybrid role based in Manchester with exciting growth opportunities.
The predicted salary is between 115000 - 125000 £ per year.
A high-growth business in the United Kingdom seeks a Head of Data Science to lead a team of data scientists and drive the transition towards machine learning engineering. This role includes setting technical direction, ensuring alignment with company objectives, and shaping the data strategy.
Candidates should have proven leadership in data science, strong expertise in ML model deployment, and the ability to partner with stakeholders.
A competitive salary of £115K - £125K plus bonus is offered.
Head of Data Science & ML Engineering (Hybrid, Manchester) employer: Data Idols
Contact Detail:
Data Idols Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data Science & ML Engineering (Hybrid, Manchester)
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science and ML engineering fields. Attend industry meetups or webinars to meet potential employers and showcase your expertise.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills and leadership experience. Be ready to discuss how you've driven data strategies and aligned projects with company objectives in the past.
✨Tip Number 3
Showcase your portfolio! If you’ve led successful projects or deployed ML models, make sure to highlight these in discussions. Real-world examples can set you apart from other candidates.
✨Tip Number 4
Don’t forget to apply through our website! We’re always looking for talented individuals who can lead and innovate in data science. Your next big opportunity could be just a click away!
We think you need these skills to ace Head of Data Science & ML Engineering (Hybrid, Manchester)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Head of Data Science role. Highlight your leadership in data science and any successful ML model deployments you've been part of.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this position. Share specific examples of how you've driven data strategy and partnered with stakeholders in previous roles.
Showcase Your Technical Skills: Don’t forget to mention your technical expertise in ML engineering. We want to see how you’ve set technical direction in past projects and how you can bring that experience to our team.
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!
How to prepare for a job interview at Data Idols
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals and the latest trends in machine learning. Be ready to discuss your past projects, especially those involving ML model deployment, as this will show your hands-on experience and technical expertise.
✨Showcase Your Leadership Skills
As a Head of Data Science, you'll need to demonstrate your leadership capabilities. Prepare examples of how you've successfully led teams, managed projects, and aligned data strategies with business objectives. This will help the interviewers see you as a strong candidate for guiding their team.
✨Understand the Business Context
Research the company and its goals thoroughly. Understand how data science and machine learning can drive their success. Being able to articulate how you can contribute to their objectives will set you apart from other candidates.
✨Prepare for Stakeholder Engagement
Since partnering with stakeholders is key in this role, think about how you've effectively communicated complex data concepts to non-technical audiences in the past. Prepare to discuss your approach to collaboration and how you ensure alignment across different teams.
