Data Scientist-Statistician

BT Group
Bristol
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist (NLP & LLM Specialist)

Data Scientist - Measurement Specialist

Data Scientist, United Kingdom - BCG X

Data Scientist, United Kingdom - BCG X

What you’ll be doing

Performing strategically important statistical analyses Developing production ready statistical and Machine Learning models  Applying formal statistical methodology and setting technical review gates as a part of a robust AI project delivery process  Conducting independent technical reviews 

Collaborating cross-functionally alongside data scientists, data engineers and cloud architects to deliver production ready technical solutions

Writing technical reports, interpreting results, and providing effective summaries for specialist and non-specialist audiences 

The skills you will need

Strong proficiency in data science concepts, machine learning, statistical analysis, and data modelling techniques, in particular with regards to the causal inference  Strong proficiency in Python or R Good knowledge of SQL Good oral and written communication skills Organised and flexible in your approach to work, with good attention to detail to ensure accuracy of data and analysis results  Bachelor’s degree in a numerate subject containing taught statistical content (e.g. Statistics, Data Science, Mathematics, Economics, Natural Sciences, …).  Demonstrable analytical experience, including the practical application of analysis or research with an in-depth knowledge of statistical modelling.  Ability to deliver quality analysis to tight deadlines, using forward planning to identify risks and issues. 

With over 175 years of heritage, BT is now the flagship business brand of BT Group. We’ve brought together our best people and capabilities into a B2B powerhouse serving 1.2 million business customers internationally. We’re a global leader for secure connectivity and collaboration platforms for businesses of all shapes and sizes, from big household names and government departments, right through to sole traders and new start-ups. But it’s not just the technology that matters, it’s what it can do to help them build stronger, smarter, more secure businesses. We value diversity and inclusion and believe in making a positive impact. We connect for good by championing digital inclusion and equipping people, businesses, and communities with digital skills to thrive. As a member of our team, you will be part of an organisation that celebrates difference, fosters innovation and provides you with opportunities to be your best. With millions of businesses relying on us daily, joining BT means you can be part of a diverse and multi-skilled team that makes a significant impact to society.A FEW POINTS TO NOTE:Although these roles are listed as full-time, if you’re a job share partnership, work reduced hours, or any other way of working flexibly, please still get in touch. We will also offer reasonable adjustments for the selection process if required, so please do not hesitate to inform us.DON'T MEET EVERY SINGLE REQUIREMENT?Studies have shown that women and people who are disabled, LGBTQ+, neurodiverse or from ethnic minority backgrounds are less likely to apply for jobs unless they meet every single qualification and criteria. We're committed to building a diverse, inclusive, and authentic workplace where everyone can be their best, so if you're excited about this role but your past experience doesn't align perfectly with every requirement on the Job Description, please apply anyway - you may just be the right candidate for this or other roles in our wider team.

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.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

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

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

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

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 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.