National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Director-Data Science and Analytics

TalkTalk
London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Director of Operations

Director of AI

Director, Machine Learning & Data Science

Director, Artificial Intelligence & Data Ethics

Director Of Machine Learning

Director, Artificial Intelligence responsible for driving the strategic development, deployment, and scaling of AI capabilities across the organization and building Centre of Excellence ground up.

Background and context


TalkTalk’s vision is to be the most recommended Wi-Fi provider in the UK by 2028 with a growing, profitable` base. Success requires that we simplify what we do, who we do it with, and reduce the cost of how we do it.

"TalkTalk is the uncomplicated way to get excellent in-home Wi-Fi coverage, we stand out from the crowd by offering intelligent but simple products that work perfectly first-time, without fuss or incomprehensible jargon, and for any help our customer service is the best in the industry”

Our aim is to deliver simplified & customer delighting Wi-Fi products and a more digital customer & employee experience. This enabled by a technology platform that leverages data to drive innovation, decision-making, and automation, ultimately providing a more cost-efficient service for our customers.


Role Overview

The Director of Data Science & Analytics will lead the data-driven transformation of the business, overseeing the strategy, governance, and execution of all data science and analytics initiatives. Reporting to the executive team, you will ensure data is leveraged to drive business growth, improve customer experience, and enable operational excellence across the organisation.


Key Responsibilities


  • Develop and execute a comprehensive data science and analytics strategy aligned with business goals.
  • Build and lead a high-performing team of data scientists, analysts, and data engineers, fostering a culture of innovation and continuous learning.
  • Oversee the end-to-end delivery of advanced analytics, machine learning, and decision support systems to improve customer engagement, retention, and revenue generation.
  • Establish robust data governance, quality, and compliance frameworks, ensuring the integrity and security of all data assets.
  • Collaborate with C-suite and business leaders to identify high-impact opportunities for data-driven decision making and process optimisation.
  • Drive the development and deployment of predictive models, customer segmentation, churn analysis, and network optimisation projects tailored to the telecoms sector.
  • Monitor key performance indicators (KPIs) and measure the business impact of analytics initiatives, focusing on tangible outcomes such as revenue growth, cost reduction, and customer satisfaction.
  • Stay ahead of industry trends, emerging technologies, and regulatory requirements relevant to data science and telecoms.


Essential Skills & Experience


  • Proven leadership in data science/analytics within a large-scale, customer-centric organisation (telecoms experience preferred).
  • Deep expertise in advanced analytics, machine learning, and AI, with a track record of delivering business value through data.
  • Strong understanding of data governance, security, and compliance in regulated environments.
  • Excellent stakeholder management and communication skills, with the ability to translate complex analytics into actionable business insights.
  • Experience building and mentoring high-performing, multidisciplinary teams.
  • Advanced degree in Data Science, Computer Science, Statistics, or a related field.
National AI Awards 2025

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.

Top 10 AI Recruitment Agencies in the UK: 2025 Edition

Generative‑AI hype has translated into real hiring: Lightcast recorded +57 % year‑on‑year growth in UK adverts mentioning “machine learning”, “LLM” or “gen‑AI” during Q1 2025. Yet supply still lags. Roughly 18,000 core AI professionals work in the UK, but monthly live vacancies hover around 1,400–1,600. That mismatch makes specialist recruiters invaluable—opening stealth vacancies, advising on salary bands and fast‑tracking interview loops. But many tech agencies sprinkle “AI” on their website without an active desk. To save you time, we vetted 50 + consultancies and kept only those with: A registered UK head office (verified via Companies House). A named AI/Machine‑Learning or Data practice.

AI Jobs Skills Radar 2026: Emerging Frameworks, Languages & Tools to Learn Now

As the UK’s AI sector accelerates towards a £1 trillion tech economy, the job landscape is rapidly evolving. Whether you’re an aspiring AI engineer, a machine learning specialist, or a data-driven software developer, staying ahead of the curve means more than just brushing up on Python. You’ll need to master a new generation of frameworks, languages, and tools shaping the future of artificial intelligence. Welcome to the AI Jobs Skills Radar 2026—your definitive guide to the emerging AI tech stack that employers will be looking for in the next 12–24 months. Updated annually for accuracy and relevance, this guide breaks down the top tools, frameworks, platforms, and programming languages powering the UK’s most in-demand AI careers.

How to Find Hidden AI Jobs in the UK Using Professional Bodies like BCS, IET & the Turing Society

Stop Scrolling Job Boards and Start Tapping the Real AI Market Every week a new headline announces millions of pounds flowing into artificial-intelligence research, defence initiatives, or health-tech pilots. Read the news and you could be forgiven for thinking that AI vacancies must be everywhere—just grab your laptop, open LinkedIn, and pick a role. Yet anyone who has hunted seriously for an AI job in the United Kingdom knows the truth is messier. A large percentage of worthwhile AI positions—especially specialist or senior posts—never appear on public boards. They emerge inside university–industry consortia, defence labs, NHS data-science teams, climate-tech start-ups, and venture studios. Most are filled through referral or conversation long before a recruiter drafts a formal advert. If you wait for a vacancy link, you are already at the back of the queue. The surest way to beat that dynamic is to embed yourself in the professional bodies and grassroots communities where the work is conceived. The UK has a dense network of such organisations: the Chartered Institute for IT (BCS); the Institution of Engineering and Technology (IET) with its Artificial Intelligence Technical Network; the Alan Turing Institute and its student-driven Turing Society; the Royal Statistical Society (RSS); the Institution of Mechanical Engineers (IMechE) and its Mechatronics, Informatics & Control Group; public-funding engines like UK Research and Innovation (UKRI); and an ecosystem of Slack channels and Meetup groups that trade genuine, timely intel. This article is a practical, step-by-step guide to using those networks. You will learn: Why professional bodies matter more than algorithmic job boards Exactly which special-interest groups (SIGs) and technical networks to join How to turn CPD events into informal interviews How to monitor grant databases so you hear about posts months before they exist Concrete scripts, portfolio tactics, and outreach rhythms that convert visibility into offers Follow the playbook and you move from passive applicant to insider—the colleague who hears about a role before it is written down.