Senior Data Scientist

Twinkl Educational Publishing
Sheffield
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist (GenAI)

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist – Twinkl Educational Publishing

Join to apply for the Senior Data Scientist role at Twinkl Educational Publishing


4 days ago – Be among the first 25 applicants


Twinkl Educational Publishing provided pay range

This range is provided by Twinkl Educational Publishing. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.


Base pay range

Job Title: Senior Data Scientist
Location: Fully flexible – remote, hybrid or office-based
Annual Salary: £60,000 – £80,000
Contract: Permanent
Twinkl is on an exciting journey to redefine how we serve our global teaching community through data. We’re building a world‑class data science function to power the next generation of our data platform, with modern tools and practices at our core.


Data Science Team


You’ll have the opportunity to work in a high‑functioning data product function, learning from experienced data scientists and engineers and using a modern data stack. We offer the freedom to work in whatever way suits you best – whether that’s remote, in our Sheffield office, or a mix of both. You’re encouraged to design algorithmic solutions, take ownership of software design, and develop your skills across the full data science stack. With our focus on impact, you’ll be part of a team that values pragmatic solutions and continuous learning, working on projects that make a real difference to educators worldwide.



  • We embrace modern data engineering practices and tools
  • We champion learning and development
  • We believe in empowering engineers to drive technical decisions
  • We focus on impact and outcomes over process

What will you be doing?

  • Work closely with engineering and product managers to develop and deliver our Search and Recommendations roadmap
  • Oversee the design and implementation of the technical work of your team, ensuring high‑quality coding, modelling, data transformation and analytics
  • Lead on delivering the coding, modelling, data transformation and analytics required, with opportunity to develop new approaches such as applying emerging techniques
  • Coach and help develop the more junior members of the team
  • Own an area of team operations (e.g., Learning & Development) and contribute to prioritisation of the Data Science roadmap

What do we need from you?
Technical skills

  • Built statistical models of real‑world processes that help inform business decisions
  • Applied machine learning to a variety of problems that generated business value
  • Worked on Search and/or Recommendations systems
  • Overseen end‑to‑end delivery of data science products
  • Experienced Python developer
  • Experienced user of SQL
  • Comfortable using version control (Git)
  • AWS experience

Personal

  • Enthusiastic, with a growth mindset and a get‑things‑done attitude
  • Comfortable working in a cross‑functional team and collaborating with colleagues in design, engineering and product
  • Innovator, ready to take responsibility and be accountable for decisions
  • Committed to helping others develop and succeed
  • Excellent communication, in both speech and writing

Most importantly, you should

  • Be curious about how things work and always look to learn more
  • Care about building models that are used by real people to deliver the right content for them
  • Understand that sometimes "boring" technology and algorithms are the right choice
  • Want to work somewhere where you can have real impact, not just maintain the status quo

What’s in it for you?

  • Friendly, welcoming and supportive culture
  • Flexible working with fully remote and hybrid options
  • 33 days annual leave per year, pro rata; entitlement increases to 38 days after 2 years
  • Additional day of annual leave – a Me Day – to take time for yourself
  • Charity day to volunteer and support a registered charity of your choice
  • Westfield Health (including Health Club discount, Westfield Rewards discount and cashback)
  • Learning and Development opportunities, including internal mobility across departments
  • 4× annual salary death‑in‑service life assurance
  • Enhanced pension after long service
  • Enhanced parental and adoption leave after long service
  • Quarterly awards to reward and recognise our employees
  • Twinkl Subscription

At Twinkl, we encourage diversity, and our doors are open to everyone. We’re committed to creating an inclusive workplace for all. If you need any adjustments during the application process to showcase your abilities, please let us know – we’re here to support you on your journey.


#J-18808-Ljbffr

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.