Head of Data Science

HCLTech
London
6 days ago
Create job alert

Current responsibilities of Head of Data Science

  • Lead the data science strategy and team to deliver data science solutions e.g. retention, acquisitions and customer management using Python and Spark
  • Lead the hiring to build a great pool of Data Scientists and Engineers for the team and support the recruitment activities of other data functions
  • Motivate, inspire, coach and mentor colleagues within the Data Science team to help them develop technical excellence
  • Define clear objectives for each individual managed, ensuring each individual has a personal development plan and regularly proactively works on it
  • Support and mentor Data Scientists and Engineers with direct reports in their role as line managers
  • Motivate, inspire, coach and mentor business partners and stakeholders to help them identify new transformational possibilities that Data Science enables
  • Engage with senior stakeholders to identify and implement machine learning solution
  • Work actively in the innovation team to catalogue, enable and propose innovation ideas
  • A Head of Data Science is a responsible authority with the requisite knowledge to work across portfolios in the domain and help provide strategic technical direction that can optimise enterprise outcomes. This particular role focuses on the portfolios within the Legal Technology Solutions area, including Lawyer Productivity, Legal Digital Products, Knowledge Systems and Data Science. It is a key role in driving digital transformation and helping to ensure that the vision is being delivered in a rapid, iterative way while focusing on the overall experience to the users.
  • Collaborate and work in tangent with different business and technical teams
  • Identifying key data sources required to solve the business and undertaking data collection, pre-processing and analysis
  • Big picture thinking - correctly diagnosing problems and productionising research.
  • In charge of demonstrations, conducting demo trials, helping clients evaluate success criteria, and training users
  • Compile, integrate, and analyse data from multiple sources to answer business questions
  • Be updated with latest technological advances, evaluate their potential by working with the hands-on
  • Quality assurance of team deliverables
  • Partner management (Microsoft, start-up discussions)
  • Manage scrum-of-scrum

Related Jobs

View all jobs

Head of Data Science

Head of Data Science & Analytics

Head of Data Science & Analytics

Head of Data Science (Credit Risk & Fraud)

Head of Credit Risk - Data Science

Head of Data Science

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.

AI Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Over the last decade, the United Kingdom has firmly established itself as one of Europe’s most significant technology hubs. Thanks to a vibrant ecosystem of venture capital, government-backed initiatives, and a wealth of academic talent, the UK has become especially fertile ground for artificial intelligence (AI) innovation. This growth is not just evident in established tech giants—new start-ups are emerging every quarter with fresh ideas, ground-breaking technologies, and a drive to solve real-world problems. In this Q3 2025 Investment Tracker, we take a comprehensive look at the latest AI start-ups in the UK that have successfully secured funding. Beyond celebrating these companies’ milestones, we’ll explore how these recent investments translate into exciting new job opportunities for AI professionals. Whether you’re an experienced machine learning engineer, a data scientist, or simply hoping to break into the AI sector, this roundup will give you insights into the most in-demand roles, the skills you need to stand out, and how you can capitalise on the current AI hiring boom.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.