At a Glance
- Tasks: Lead a dynamic team of data scientists and shape the data science strategy.
- Company: High-growth business focused on innovative data solutions.
- Benefits: Competitive salary, bonus, and opportunities for career growth.
- Other info: Flexible working with 2-4 days in Manchester each month.
- Why this job: Make a real impact by driving machine learning engineering and model deployment.
- Qualifications: Proven leadership in data science and experience with ML models.
The predicted salary is between 110000 - 120000 £ per year.
Salary: £110K - £120K + bonus
Location: Manchester 2-4 days a month
The Opportunity
We are working with a high-growth business that is scaling its data function to the next level. Data scientists here have traditionally combined reporting with predictive modelling, but the business is now creating a dedicated leadership role to bring focus, structure and engineering rigour to the discipline.
As Head of Data Science, you will lead a growing team of 6+ scientists embedded across product and functional teams, while also setting the technical direction and ensuring alignment with company-wide OKRs. You will drive the transition towards machine learning engineering, championing end-to-end model ownership from research through to deployment in production. This is a fantastic opportunity to shape the data science strategy, support the career growth of talented scientists, and deliver measurable impact in areas such as search, pricing, personalisation, vouchers, marketing, operations and finance.
Skills and Experience
- Proven leadership experience in data science or machine learning, ideally within product-led or consumer-facing organisations
- Strong background in building and deploying ML models at scale in production environments
- Ability to structure and lead embedded data science teams, partnering effectively with senior stakeholders across multiple domains
- Hands-on technical expertise with tools such as Databricks, Python, Spark, and GCP/BigQuery
- Engineering mindset, with experience moving teams toward machine learning engineering best practice
- Credibility to lead long-tenured individual contributors while providing direction, mentorship and career development
If you are looking for a new challenge, then please submit your CV for initial screening and more details.
Head of Data Science in Edinburgh employer: Data Idols
Join a high-growth business in Manchester that prioritises innovation and employee development, offering a competitive salary and bonus structure. With a collaborative work culture and a focus on machine learning engineering, you'll have the opportunity to lead a talented team of data scientists while shaping the company's data strategy. This role not only allows for significant career growth but also enables you to make a tangible impact across various business functions.
StudySmarter Expert Advice🤫
We think this is how you could land Head of Data Science in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, attend meetups, and engage in online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Showcase your skills! Create a portfolio that highlights your best projects, especially those involving machine learning and data engineering. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and leadership questions. Be ready to discuss your experience with tools like Python and Databricks, and how you've led teams to success in previous roles.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Head of Data Science in Edinburgh
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the Head of Data Science role. Highlight your leadership experience and any hands-on work with ML models. We want to see how your skills align with our needs!
Showcase Your Impact:When detailing your past roles, focus on the measurable impact you've had. Use numbers and examples to illustrate how you've driven success in data science or machine learning projects. This helps us see the value you can bring!
Be Authentic:Let your personality shine through in your application. We’re looking for someone who can lead a team and inspire others, so don’t be afraid to show us who you are and what motivates you!
Apply Through Our Website:For the best chance of getting noticed, make sure to apply through our website. It’s the easiest way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Data Idols
✨Know Your Data Science Stuff
Make sure you brush up on your technical skills, especially around machine learning and model deployment. Be ready to discuss your experience with tools like Python, Spark, and Databricks, as well as any projects where you've led a team or implemented ML models in production.
✨Showcase Your Leadership Skills
As the Head of Data Science, you'll need to demonstrate your ability to lead and mentor a team. Prepare examples of how you've successfully managed teams in the past, particularly in product-led environments, and be ready to discuss how you can support the career growth of your team members.
✨Align with Company Goals
Familiarise yourself with the company's OKRs and think about how your vision for the data science function aligns with these objectives. During the interview, articulate how you plan to drive measurable impact in key areas like pricing and personalisation, showing that you understand the business's needs.
✨Prepare for Technical Questions
Expect some deep dives into your technical expertise. Be prepared to answer questions about your approach to building and deploying ML models, and consider discussing any engineering best practices you've implemented. This will show that you not only have the skills but also the engineering mindset needed for the role.
