Head of Data Science

Charing Cross
1 month ago
Create job alert

About The Role
Team – Data Science
Working Pattern - Hybrid – 2 days per week in the Vitality London Office. Full time, 37.5 hours per week. 
We are happy to discuss flexible working!
Top 3 skills needed for this role:

Deep experience of developing and deploying impactful machine learning applications in a commercial environment.
Proven past experience of leading a high-performing data science team.
Experience developing and deploying models in a cloud based environment.What this role is all about:
The Head of Data Science at Vitality is a leadership role responsible for supporting the mission of helping Vitality members live happier, healthier lives. This position involves collaborating with Health and Life business stakeholders, from executive level down, to identify high value-add data science projects aligned with organisational priorities. The Head of Data Science also sells the vision of these projects to key decision makers to ensure they are prioritised by IT delivery teams.
Additionally, this role involves prioritising and directing the work of six data scientists, ranging in seniority from data scientist to lead data scientist, and enabling their work by ensuring they have access to the required technology and resolving issues during the deployment process. Furthermore, the Head of Data Science supports the rollout of a new Google Cloud-based machine learning platform, leading the team to full adoption of advanced ML Ops capabilities, and ensuring the platform is fully integrated into existing Vitality infrastructure. 
Key Actions

Key contributor to data science roadmap, setting out project priorities into the medium-term.
Drives roadmap projects through to successful deployment and demonstrates the impact of live projects to the bottom line of the business.
Constantly working with business stakeholders to identify new project ideas, which are maintained as a backlog and fed into the delivery roadmap as part of a periodic prioritisation process.
Builds and manages relationships with a wide range of stakeholders across the Health and Life businesses as well as operational support functions and IT delivery teams.
Is responsible for the monitoring and management of live models, taking initiative to refit and calibrate to latest experience.
Works closely with data warehousing and data engineering teams to ensure the team has access to the data it needs to deliver current and future projects.
Manages data science team members, ensuring alignment with departmental and business-wide vision and strategies.
Gain a deep understanding of Vitality’s data assets to inform project identification and selection.
Drafts and presents reports to senior management on project performance.
Develops and maintains a deep understanding of the business’s dynamics, supporting proactive project identification across the entire value chain.
Keep up to date with the latest developments in the world of AI.
Responsible for driving education and evangelisation of data science throughout the business.What do you need to thrive?

Experience solving a wide range of business problems using machine learning approaches.
Strong communications skills, able to communicate at all levels of the organisation, across technical and non-technical audiences.
Proven past experience of identifying high-impact projects, building a business case for those projects, and getting buy-in for their delivery.
Proven experience working in and/or leading cross-functional technical delivery teams.
Positive, can do attitude. Likes to proactively take ownership for resolving the blockers inevitably arising during model deployment.
Stays up to date on latest developments in AI.
Flexible, outcomes driven approach to problem solving.
Good appreciation of software engineering best practices.
Fluent in Python and SQL
Educated to a degree level in relevant STEM subject.So, what’s in it for you?

Bonus Schemes – A bonus that regularly rewards you for your performance
A pension of up to 12%– We will match your contributions up to 6% of your salary
Our award-winning Vitality health insurance – With its own set of rewards and benefits
Life Assurance – Four times annual salaryThese are just some of the many perks that we offer!
If you are successful in your application and join us at Vitality, this is our promise to you, we will:

Help you to be the healthiest you’ve ever been.
Create an environment that embraces you as you are and enables you to be your best self.
Give you flexibility on how, where and when you work.
Help you advance your career by playing you to your strengths.
Give you a voice to help our business grow and make Vitality a great place to be.
Give you the space to try, fail and learn.
Provide a healthy balance of challenge and support.
Recognise and reward you with a competitive salary and amazing benefits.
Be there for you when you need us.
Provide opportunities for you to be a force for good in society. 
Diversity & Inclusion
At Vitality, we’re committed to diversity and inclusion because it’s good for our employees, for our business, and for society. We welcome applications from individuals of all backgrounds, experiences, and perspectives.
Vitality’s approach to sustainability
Vitality is a business that drives positive change. We reward people for making and sustaining healthier choices. But healthy people also need a healthy environment. To learn more please visit our Careers page. 
If we are fortunate in receiving a high volume of quality applications we may need to close this vacancy early

Related Jobs

View all jobs

Head of AI

Lead Data Engineer

Senior Data Analyst

Product Management Assistant

Senior Business Systems Analyst

Senior Business Systems Analyst (Field Engineer Planning Systems)

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.

Shifting from Academia to the AI Industry: How Researchers Can Harness Their Skills to Drive Commercial Artificial Intelligence

Artificial intelligence (AI) has advanced from a specialised academic pursuit to a transformative force in almost every sector—from healthcare diagnostics and autonomous vehicles to recommendation systems and creative generative models. As AI technologies continue to grow in complexity and impact, companies are looking for talent that combines deep theoretical knowledge with the ingenuity to solve real-world challenges. Increasingly, PhDs and academic researchers fit this profile perfectly. This guide will help you map out the transition from academia to industry in artificial intelligence. Whether you specialise in reinforcement learning, computer vision, natural language processing, or another AI discipline, you’ll find actionable advice on how to translate your academic strengths, adapt to commercial constraints, and excel in roles where your research insights can revolutionise products, services, and user experiences.

The Ultimate Glossary of AI Terms: Your Comprehensive Guide to Artificial Intelligence

Artificial Intelligence (AI) is transforming the modern workforce and daily life at an unprecedented pace. From healthcare to finance, AI-driven solutions are helping organisations streamline processes, enhance decision-making, and offer innovative products and services. As a result, AI jobs are in high demand, offering lucrative salaries and exciting career paths for those with the right skill set. Whether you’re starting your journey toward an AI career or you’re a seasoned professional aiming to stay on top of the latest developments, a strong command of AI terminology is essential. This glossary of key AI terms will help you navigate important concepts, from fundamental machine learning techniques to advanced topics like deep learning and ethical AI. By familiarising yourself with this comprehensive list, you’ll be better equipped to discuss AI trends, contribute to innovative projects, and identify new opportunities in one of tech’s fastest-growing fields.

Diversity & Inclusion in AI Jobs: Building a More Equitable Workforce for Recruiters and Job Seekers

Artificial Intelligence (AI) is rapidly reshaping how we live, work, and interact with technology. From virtual assistants in our homes to complex machine learning algorithms powering healthcare diagnostics, AI is becoming increasingly integrated into our daily lives. As the field expands, AI systems and solutions are touching more people and influencing more industries than ever before. Despite the vast potential of these technologies, one critical area that requires urgent attention is diversity and inclusion (D&I) within AI teams and organisations. The current state of diversity in AI can be best described as a work-in-progress. For years, the technology sector as a whole has struggled to achieve balanced representation across gender, race, socioeconomic status, and other underrepresented groups in tech. While there has been some improvement—thanks to awareness campaigns, diversity programmes, and mentorship initiatives—recent studies still reveal a stark gap in the presence of women, ethnic minorities, people with disabilities, and other marginalised communities in AI roles. According to various reports, women represent only a fraction of the AI workforce, and people from Black or other ethnic minority groups remain disproportionately underrepresented in tech leadership positions. The lack of diversity in AI reflects broader inequalities within STEM (science, technology, engineering, and mathematics) fields, and these issues can have direct consequences on the products and services we create. Why does this matter so much? AI systems are often trained on large datasets that can inadvertently carry biases. If the teams building AI are not representative of the society their products serve, it can lead to entrenched biases—sometimes in unexpected ways. For example, facial recognition software has historically struggled to accurately recognise non-white faces. Chatbots and language models have, at times, echoed prejudices lurking in their training data. When AI products and services fail to consider the full spectrum of users, the results can undermine public trust, stall innovation, and cause real-world harm. On the flip side, the benefits of inclusive teams for innovation and product design are considerable. Diverse and inclusive environments tend to foster a broader range of perspectives, ensuring that potential blind spots are addressed early in the AI development process. This leads to more robust, user-friendly products that cater to a wider audience. Multiple studies have shown that companies prioritising diversity are not only more innovative but also more profitable. By embracing underrepresented groups in tech, employers can tap into a broader talent pool, spark creative solutions, and boost employee satisfaction. But how do we go about creating more inclusive AI workplaces? In this article, we will explore the barriers to entry that many underrepresented groups face, examine successful D&I initiatives shaping the industry, and provide practical advice on how job seekers and employers alike can champion diversity in AI. Our goal is to illuminate pathways to a more equitable AI workforce, one where talent and merit thrive unhindered by systemic barriers. By taking deliberate steps to break down these barriers and actively promote inclusivity, we can ensure that AI technology reaches its full potential for everyone. Whether you are an aspiring AI professional, a hiring manager, or simply curious about how the tech industry is evolving, the following insights will help you better understand why diversity in AI is so vital. Moreover, you’ll learn about concrete steps you can take—or encourage your company to take—to nurture a thriving, diverse workforce. Ultimately, creating an inclusive environment is not just a corporate social responsibility; it is the key to unlocking the next wave of AI-driven innovation and ensuring the technology serves all communities in a fair and ethical manner.