Data Scientist

TalkTalk Group
Salford
6 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (eDV clearance required)

Who are TalkTalk?

TalkTalk are the UK’s leading value for money connectivity provider. We believe that simple, affordable, reliable and fair fibre should be available to everyone.

The role

TalkTalk is passionate about using data driven insight to underpin our decision making; from the day to day running of our business through to answering the larger more complex business questions.

The Data Science team works closely with Product & Commercial, Marketing and Sales & Loyalty teams to increase the satisfaction and value of our customers.

Your responsibilities

As a Data Scientist you'll work directly with stakeholders to design and test business hypotheses to identify and implement new trigger-based campaigns to solve core business challenges.

Your work will deliver churn, satisfaction and revenue improvement using machine learning to industrialise predictive and prescriptive models and segmentations.

You'll be a customer advocate, helping colleagues to understand and connect with our customers at the overall & segment level.

You'll also work closely with the other analysts and researchers in the team to deliver the Customer Insight Strategy.

The successful individual will be passionate about data and analytics, highly experienced in delivering actionable insight and comfortable working in a fast paced environment. You'll have a desire to continue to develop yourself and others across the analytics community, growing our Data science capability.

What do I need in order to be successful?

Must have:

A BSC or MSC in a numerate discipline (Mathematics, Statistics, Computer Science Engineering)

Strong experience in customer analytics/ insight

Proficient in SQL and at least one of the following: Python, R, Scala 

Expert in statistical modelling including k-means segmentation, multiple regression, factor analysis, time-series, forecasting and gradient boosting

Ability to build strong personal relationships and trust with business and technical colleagues

Skilled in communicating complex insight succinctly and clearly

It would be great if you also have (but we'd still like to hear from you if you don't):

Experience in the Telecommunications sector

Background in agency or consultancy

Experience in deep learning, neural networks, reinforcement and adaptive learning

Experience in digital data sets, e.g. social listening and social network analysis, plus natural language processing.

Familiarity with Cloud platforms(Microsoft Azure, GCP or AWS)and data visualisation using PowerBI

Experience in Marketing ROI initiatives such as Econometrics, Marketing Mix Modelling, Attribution

What can offer ?

Free TalkTalk broadband for all employees!

Electric car charging points available at our HQ.

Heavily subsidised meals in the TalkTalk HQ Soapworks office in Salford.

Access to the Perks at Work platform which gives you hundreds of discounts on high street brands.

Flexible dynamic working is part of who we are at TalkTalk so please talk to us about how you like to work.

What to do next?

If this role sounds like it could be for you, please apply and we will be in touch soon!

As a recognised Top 50 Inclusive Employer in the UK, we know that diversity means success and innovation. We want our workplace to reflect the communities and customer we serve. Being inclusive is part of our DNA; we are all 100% human, and we create a culture where you can truly be yourself.

We’re also not your usual 9-5. We are a dynamic workplace and we want to talk to you about how you like to work.

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Tips for Staying Inspired: How Machine Learning Pros Fuel Creativity and Innovation

Machine learning (ML) continues to reshape industries—from personalised e-commerce recommendations and autonomous vehicles to advanced healthcare diagnostics and predictive maintenance in manufacturing. Yet behind every revolutionary model lies a challenging and sometimes repetitive process: data cleaning, hyperparameter tuning, infrastructure management, stakeholder communications, and constant performance monitoring. It’s no wonder many ML professionals can experience creative fatigue or get stuck in the daily grind. So, how do machine learning experts keep their spark alive and continually generate fresh ideas? Below, you’ll find ten actionable strategies that successful ML engineers, data scientists, and research scientists use to stay innovative and push boundaries. Whether you’re an experienced practitioner or just breaking into the field, these tips can help you fuel creativity and discover new angles for solving complex problems.

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.