At a Glance
- Tasks: Lead a dynamic team in building innovative AI and Data Science solutions.
- Company: Join a forward-thinking company at the forefront of data science and AI.
- Benefits: Enjoy competitive salary, flexible working, and opportunities for professional growth.
- Other info: Be part of a collaborative culture with excellent career advancement opportunities.
- Why this job: Make a real impact by driving innovation in AI and data governance.
- Qualifications: Experience in data science and a passion for leadership are essential.
The predicted salary is between 80000 - 100000 £ per year.
Job Type: Permanent
Reporting to: RE&ILS Head of Data
Location: London
Role Overview: The Lead Data Scientist is a crucial member of the extended RE&ILS Tech Leadership Team, responsible for building, leading, and nurturing a highly capable Data Science and Machine Learning chapter. This role facilitates the successful delivery of new AI Cloud-based solutions against our growing list of business use cases involving complex Data Analytics, Machine Learning, and AI Agent based solutions. You will co-lead the new Data Science chapter with the RE&ILS Head of Data and help ensure its members provide Data Science capabilities and insights to support decision-making across RE&ILS strategic Value Streams. Whilst the chapter grows, you are expected to be hands-on actively helping to architect, design, and build AI or Data Science-based solutions, using internally trained models, LLMs and/or a combination of both. It is essential that you and your entire chapter operate within the boundaries of the Group AI Governance Framework and maintain rigorous data governance standards. You will be accountable for this adherence.
Key Responsibilities:
- Chapter Leadership & Talent Management
- People Management: Lead, recruit, mentor, coach, train, and retain a high-performing chapter of Data Scientists and Machine Learning Engineers.
- Culture & Development: Cultivate a collaborative, engaged, and fulfilled team culture. Provide technical leadership, career guidance, and direction to the team.
- Best Practice: Ensure the chapter adheres to best practices in data science, AI, and complex analytics.
- Mentoring: Mentor and educate others in various data science techniques, encouraging the team to continually learn.
- Solution Delivery & ML Ops Excellence
- Hands-On Architecture: Get hands-on to help architect, design, and build complex models that integrate into existing IT solutions.
- ML Ops Platform: Actively work with the Head of Platform Engineering to establish and maintain a professional ML Ops platform.
- Speed of Execution: Empower the chapter to work effectively within autonomous squads.
- Pipeline Collaboration: Work with Data Engineering and other teams to understand and contribute to the requirements and building of necessary data pipelines/products.
- Strategy, Governance & Innovation
- Use Case Identification: Work with key business leaders to identify new use cases and opportunities where data science/AI can deliver a competitive advantage.
- Governance & Compliance: Champion data and model governance, ensuring a mature understanding of data governance.
- Innovation: Maintain a strong awareness of new trends and techniques in Data Science, AI, and Machine Learning.
- Communication: Ensure clear and effective communication of data science solutions and outcomes across business layers.
Required Experience & Structure:
Reporting to: RE&ILS Head of Data; dotted line to Group Head of Data Science. Direct line management for Data Scientists and Machine Learning Engineers within the RE&ILS Data Science Chapter.
Candidate Profile: The successful candidate will be an energetic, highly capable, and passionate Senior Data Scientist who wants to move into their first people management role. You must be comfortable working in an FCA-regulated business, advocating for a data-driven approach, and driving innovation while maintaining rigorous AI governance standards.
Key Experience:
- Deep Interest in Leadership: Demonstrated mentoring and coaching of junior team members.
- Technical Depth: Extensive hands-on experience in architecting, designing, and building complex ML models.
- ML Ops Maturity: Proven ability to build, maintain, and support production-deployed models.
- AI and Data Governance: Mature understanding of AI and data governance.
- Stakeholder Management: Experience managing collaboration with business unit leaders and external technology partners.
Education: Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent.
Technical Proficiency: Exceptional proficiency in Python (and R), SQL capabilities, mastery of machine learning & statistical modelling techniques.
Lead Data Scientist employer: Hiscox Underwriting Group Services Ltd (HUGS)
At Hiscox, we pride ourselves on being an exceptional employer, particularly for the Lead Data Scientist role based in London. Our vibrant work culture fosters collaboration and innovation, providing ample opportunities for professional growth and development within a supportive environment. With a commitment to best practices in data science and AI, employees are empowered to lead pioneering projects while enjoying the benefits of working in a dynamic, FCA-regulated business that values data-driven decision-making.
Contact Details:
Hiscox Underwriting Group Services Ltd (HUGS) Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the data science community. Attend meetups, webinars, or conferences where you can chat with industry leaders and potential colleagues. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving AI and machine learning. This is your chance to demonstrate your hands-on experience and technical depth, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your leadership and mentoring skills. Since this role involves managing a team, be ready to discuss how you've successfully guided others in the past and how you plan to cultivate a collaborative culture.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are genuinely interested in joining our team at StudySmarter!
We think you need these skills to ace Lead Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience in data science, machine learning, and any leadership roles you've had. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how you can contribute to our Data Science chapter. Be genuine and let your personality come through.
Showcase Your Technical Skills:Don’t forget to highlight your technical expertise, especially in Python, SQL, and ML models. We’re looking for someone who can get hands-on, so share examples of your past projects that demonstrate your capabilities.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Hiscox Underwriting Group Services Ltd (HUGS)
✨Know Your Data Science Fundamentals
Brush up on your core data science concepts, especially around machine learning and AI. Be ready to discuss your hands-on experience with complex models and how you've applied them in real-world scenarios. This will show that you not only understand the theory but can also implement it effectively.
✨Showcase Your Leadership Skills
Since this role involves leading a team, be prepared to share examples of how you've mentored or coached others in the past. Highlight any experiences where you successfully managed projects or guided junior team members, as this will demonstrate your readiness for a managerial position.
✨Understand the Company’s AI Governance Framework
Familiarise yourself with the principles of AI governance and data privacy laws relevant to the company. Be ready to discuss how you would ensure compliance while driving innovation in data science solutions. This shows that you’re not just technically proficient but also aware of the regulatory landscape.
✨Prepare for Collaborative Discussions
Expect to engage in conversations about cross-functional collaboration. Think of examples where you've worked with other teams, like Data Engineering or Product Management, to deliver successful outcomes. This will highlight your ability to work within autonomous squads and contribute to a cohesive team environment.
