Data & Insights Manager

ADLIB
Bradford
9 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

HR and Payroll Data Analyst

Senior Data Analyst

Senior Data Scientist

Data Engineer Manager

Data Engineer Manager

Data Insight in The Education Sector

  • Leading & mentoring a talented data team.
  • Hands-on role with Python, SQL, and data visualisation.
  • Work in a purpose-driven company, working for a BCorp certification and making real impact.


Are you a data enthusiast who thrives in turning complex information into meaningful insights? Do you want to work for a company where your skills can directly improve education outcomes for millions of students? Were looking for a Data & Insights Manager to lead a talented team, drive data strategy, and get hands-on with cutting-edge data tools.
What youll be doing:
As Data & Insights Manager, youll be leading a small but talented team, helping them grow, collaborate, and deliver high-quality data solutions. This role is hands-on, so youll also be hands on and diving into data, uncovering insights, and making a real impact across the business.
Youll be working with a massive dataset spanning millions of users, turning complex information into meaningful insights that help schools, teachers, and students. Your work will shape key decisions internally and externally, ensuring data is used effectively to improve education outcomes.
As well as this, youll be driving the companys data strategy, making sure everything is scalable, reliable, and forward-thinking. Youll champion a data-driven culture, empowering teams to use data with confidence and keeping an eye on emerging trends like AI. If you love working with data, thrive in a collaborative environment, and want to make a real difference, this is the perfect role for you and wed love to hear from you!
What experience youll need to apply:

  • Strong technical expertise inPython, SQL, ETL, and Googles data stack (BigQuery, Dataform, Looker Studio, Composer).
  • Experience leading and mentoring data teams, with a passion for developing people.
  • A deep understanding ofdata science, data engineering, and analyticswith hands-on experience working with real-world datasets.
  • Strong problem-solving skills and experience optimising workflows and ensuring data quality.
  • Excellent communication skills, able to translate technical findings into clear, compelling insights for a range of audiences.
  • A purpose-driven mindset and a passion for using data to make a real impact.


What youll get in return:
A salary of up to £80,000 per anuum. An amazing office including free food, flexibility for things like school runs and the need to be at home when required, but working from the office 5 days a week where possible.
Whats next?
Apply with your updated resume, and well review your application as soon as possible to set up a call and discuss the role further! For any questions, feel free to email Tegan.

JBRP1_UKTJ

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Jobs

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Jobs

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.