At a Glance
- Tasks: Lead high-impact data science projects and mentor junior data scientists.
- Company: Global insurance firm known for innovation in data and analytics.
- Benefits: Competitive salary, flexible working, generous leave, and professional development.
- Other info: Join a diverse team committed to building a data-driven culture.
- Why this job: Shape the future of data science in a collaborative and innovative environment.
- Qualifications: Experience in data science, machine learning, and strong communication skills.
The predicted salary is between 43200 - 72000 £ per year.
Our client is a global organisation operating within the insurance and financial services sector, recognised for its strategic investment in data, analytics, and emerging technologies. The business leverages advanced analytics and artificial intelligence to enhance decision‑making, optimise operational processes, and deliver innovative solutions across its global operations. With a strong commitment to building a data‑driven culture, the organisation brings together multidisciplinary teams of data scientists, engineers, and technology specialists to develop scalable analytics solutions that drive measurable business impact. Employees are encouraged to collaborate across functions, contribute innovative ideas, and continuously develop their technical and leadership capabilities.
Our client is seeking a Principal Data Scientist to lead the delivery of complex, high‑impact data science initiatives across multiple business functions. In this role, you will provide technical leadership and strategic direction for advanced analytics and machine learning solutions that support key business priorities. You will be responsible for guiding the end‑to‑end development of data science projects, from translating complex business challenges into technical solutions through to delivering scalable models and analytical frameworks. In addition to hands‑on technical work, you will play a key role in mentoring data scientists, setting technical standards, and strengthening the organisation’s analytics capability. Working closely with cross‑functional teams across engineering, data, and business functions, you will help ensure data science solutions deliver measurable value and are effectively embedded into operational processes.
Key Responsibilities
- Apply industry best practices, emerging methodologies, and research‑driven approaches to develop data science solutions that support business innovation.
- Provide technical leadership across the end‑to‑end lifecycle of complex data science initiatives, from problem definition through to deployment and evaluation.
- Translate complex business challenges into structured analytical and modelling approaches.
- Work with large and diverse datasets, including both internal and third‑party data sources.
- Develop and implement advanced machine learning and statistical modelling techniques to generate actionable insights and deliver measurable business impact.
- Provide mentorship and technical guidance to junior and mid‑level data scientists, promoting best practices and continuous skill development.
- Collaborate closely with data engineers, analysts, and business stakeholders to ensure successful delivery and adoption of analytical solutions.
- Contribute to the development of analytical frameworks that measure the commercial impact and efficiency of data science solutions.
- Support the growth of the organisation’s data and analytics community by sharing knowledge and promoting advanced analytical capabilities.
Required
- Bachelor’s or Master’s degree in a quantitative discipline such as Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field, or equivalent practical experience.
- Extensive professional experience in data science or advanced analytics, including a proven track record delivering complex and impactful data science solutions.
- Strong experience applying machine learning, statistical modelling, and advanced analytical techniques to solve business problems.
- Demonstrated ability to lead technical delivery of complex analytics initiatives from concept through to production deployment.
- Experience mentoring or supporting the technical development of data scientists.
- Strong understanding of Agile development methodologies and software engineering best practices relevant to data science.
- Excellent communication skills with the ability to translate complex analytical findings into clear, actionable insights for both technical and non‑technical stakeholders.
- Experience collaborating with cross‑functional teams including engineering, product, and business stakeholders.
Preferred
- Experience applying data science within financial services or insurance environments.
- Experience implementing frameworks to measure the commercial impact of machine learning and analytics initiatives.
- Familiarity with deploying scalable machine learning models in cloud or production environments.
Key Technical Skills
- Advanced proficiency in Python (and optionally R) for data science and analytics.
- Strong SQL capabilities for data extraction and manipulation.
- Deep expertise across a range of machine learning and statistical modelling techniques, including classical models, ensemble methods, and deep learning.
- Experience with Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP), or Computer Vision applications.
- Strong understanding of statistics, experimental design, and model evaluation techniques.
- Familiarity with cloud platforms and scalable data environments.
Impact and Achievements
- Lead the development and deployment of high‑impact machine learning and AI‑driven solutions that generate measurable commercial value.
- Translate complex analytical insights into tangible improvements across business processes and performance metrics.
- Elevate the technical maturity and capability of the data science function by introducing industry‑leading methodologies, tools, and best practices.
- Support the growth and development of the wider analytics team through mentorship and technical leadership.
Competitive salary and performance‑related incentives. Pension contributions. Generous annual leave allowance. Flexible and hybrid working arrangements. Professional development and leadership growth opportunities. Collaborative and innovative technical environment. Opportunity to shape enterprise‑level data science strategy and capabilities.
Equal Opportunity Statement
SPG Resourcing is an equal opportunities employer and is committed to fostering an inclusive workplace which values and benefits from the diversity of the workforce we hire. We offer reasonable accommodation at every stage of the application and interview process.
Principal Data Scientist employer: SPG Resourcing
Our client is an exceptional employer, offering a dynamic and collaborative work culture that prioritises innovation and professional growth. With a strong commitment to employee development, the organisation provides ample opportunities for mentorship and leadership advancement, all within a flexible hybrid working environment in London. Joining this global insurance firm means being part of a forward-thinking team that leverages cutting-edge data science to drive impactful business solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Data Scientist
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those that highlight your machine learning and analytical prowess. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨Tip Number 4
Don't forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Principal Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Principal Data Scientist role. Highlight your experience in data science, machine learning, and any relevant projects you've led. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your background fits with our mission at StudySmarter. Be sure to mention specific examples of your work that demonstrate your leadership and technical skills.
Showcase Your Technical Skills:Since this role requires strong technical expertise, don’t shy away from detailing your proficiency in Python, SQL, and any machine learning techniques you've mastered. We love seeing candidates who can clearly articulate their technical capabilities and how they’ve applied them in real-world scenarios.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at SPG Resourcing
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning and statistical modelling techniques. Be ready to discuss specific projects where you've applied these skills, especially in complex environments like financial services or insurance.
✨Showcase Your Leadership Skills
As a Principal Data Scientist, you'll be expected to lead teams and mentor others. Prepare examples of how you've guided junior data scientists or led analytics initiatives from concept to deployment. Highlight your ability to communicate complex ideas clearly.
✨Understand the Business Impact
Be prepared to talk about how your data science solutions have driven measurable business value. Think of specific instances where your work has improved processes or outcomes, and be ready to explain the commercial impact of your projects.
✨Collaborate Like a Pro
This role involves working closely with cross-functional teams. Have examples ready that demonstrate your experience collaborating with engineers, analysts, and business stakeholders. Show how you’ve successfully integrated data science solutions into operational processes.
