Junior Data Scientist

Years.com - More Years Together
Nottingham
3 days ago
Create job alert
Join Our Pack šŸ¶šŸ½ļø

From a bold idea to revolutionising dog food, Years has grown into a fast‑scaling business dedicated to helping dogs live longer, healthier lives.


In just 3 years, we've built a great start up business, serving thousands of happy customers, all while striving to achieve our mission.


Our goal? To give dog owners a better, fresher, and healthier way to feed their pets. We provide human cut, personalised meals designed to support each dog's unique needs, delivered straight to their door — no preservatives, no compromises, just real nutrition.


You can find our customers across the UK, with future ambitions to scale internationally and continue transforming how people care for their dogs.


Your Mission

We are looking for a motivated and curious Junior Data Scientist to join our growing data team. In this role, you'll help analyse data, build models, and generate insights to support data‑driven decisions across the business.


As data is used everywhere to provide insights within business, the opportunities to interact with different departments will be dynamic and varied. This is an excellent opportunity for someone early in their career who is excited to learn, collaborate, and grow in a dynamic environment.


Key Responsibilities

Collect, clean, and preprocess data from various sources, working to expand the existing data team:



  • Conduct exploratory data analysis to identify trends, patterns, and insights
  • Build and validate basic statistical models and machine learning models under guidance from senior team members
  • Communicate findings through reports, dashboards, and visualisations
  • Collaborate closely with the wider business and business stakeholders to understand requirements and deliver actionable insights
  • Document data processes, analyses, and methodologies to ensure reproducibility and transparency

Requirements

  • Degree in Data Science, Statistics, Computer Science, Mathematics, or a related field
  • Proficiency in Python, R, or a similar programming language for data analysis
  • Experience working with data visualisation tools (e.g., Tableau, Power BI, matplotlib, seaborn)
  • Familiarity with SQL and relational databases
  • Strong analytical and problem‑solving skills
  • Excellent communication skills and ability to present technical concepts to non‑technical audiences
  • Eagerness to learn new tools, techniques, and concepts
  • Flexible and dynamic mindset

Bonus if you have...

  • Internship or academic project experience involving data analysis or modelling
  • Exposure to cloud platforms
  • Experience with version control tools like Git

Benefits

What's In It For You? Years Benefits



  • Ā£33,000 – Ā£38,000 PA
  • Annual Ā£250.00 Learning & Development budget for courses, books or other self‑learn activities
  • Access to Spill EAP and Mental Wellbeing support
  • Annual Ā£200.00 Wellbeing budget
  • MediCash medical cashback plan
  • Up to 2 weeks working abroad per year (selected roles)
  • Monthly recognition through our Yappa of The Month programme
  • 1 Volunteer day per year – dog themed or not: it’s your choice!
  • Subsidised employee groups – from five a side to padel there's loads to get involved in or the chance to start up your own group
  • Exclusive discounts on Years and Years treats for yourself and friends/family
  • Lunch & Learn programme – from dog first aid to financial savviness we’ve got sessions planned to cover all kinds of topics
  • Casual dress
  • Your birthday off or different day if it falls on a non‑working day
  • Ability to sell any unused holiday back to Years at the end of the Holiday Year (maximum 1 working week)


#J-18808-Ljbffr

Related Jobs

View all jobs

Junior Data scientist

Junior Data Scientist / Data Analyst

Junior Data Scientist

Junior Data Scientist

Junior Data Scientist

Junior Data Scientist: Sports Analytics & Trading

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 AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new ā€œmust-learnā€ platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.