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- Tasks: Lead advanced AI projects, from model design to deployment and monitoring.
- Company: Join Insurwave, a cutting-edge Insurtech revolutionising risk management with AI.
- Benefits: Enjoy 25 days leave, private healthcare, flexible working, and a supportive team culture.
- Why this job: Make a real impact in a values-driven environment while innovating in data science.
- Qualifications: 5+ years in data science, strong ML skills, and a passion for learning.
- Other info: Collaborate with a multidisciplinary team and mentor junior data scientists.
The predicted salary is between 48000 - 84000 £ per year.
Direct message the job poster from Insurwave
At Insurwave, we are looking for remarkable people who thrive on making an exceptional contribution. We now have an exciting opportunity for a Senior Data Scientist to play a key role in our Data and AI team. If making a difference gets you out of bed in the morning, then this could be the perfect opportunity and the start of something incredible!
What will you be doing?
As a Senior Data Scientist, you will be a technical expert in a multidisciplinary team developing advanced AI and analytics solutions for the Insurwave platform. You’ll take full ownership of complex machine learning initiatives, from problem framing and algorithm selection to scalable deployment and monitoring. You will work across the full machine learning lifecycle, designing sophisticated models, experimenting with cutting edge techniques and building robust, production-ready pipelines. You will also contribute to the technical architecture, champion best practices in MLOps, and guide the strategic direction of our AI capabilities. This is a hands-on role for someone who enjoys both deep technical work and cross-functional collaboration—driving forward innovation while ensuring reliability, performance, and business value
Responsibilities
- Architect and implement state-of-the-art machine learning solutions across use cases including intelligent document processing, risk modelling, and asset behaviour analytics
- Conduct advanced experimentation and model development, applying deep learning, LLMs, or probabilistic methods as appropriate
- Build high-performance, production-grade pipelines for data ingestion, feature engineering, model training, and real-time inference
- Develop and maintain robust APIs and infrastructure for scalable model deployment, monitoring, and versioning
- Apply rigorous model evaluation, performance tuning, and A/B testing methodologies
- Continuously monitor model behaviour post-deployment, addressing drift, feedback loops, and retraining strategies
- Contribute to and influence architectural decisions regarding ML systems and tooling (e.g., feature stores, orchestration frameworks, vector databases)
- Lead technical discussions, code reviews, and mentoring sessions for junior and mid-level data scientists
- Lead R&D initiatives by exploring and prototyping novel techniques from open-source innovation and emerging trends .
What skills and experience will I need to bring with me?
You’ll need to be able to demonstrate the core skills for the role, although more importantly if you don’t quite have all the skills, you have a passion and willingness for learning. Here’s what the teams will be looking for:
- 5+ years hands on experience in data science or ML role with a strong focus on building and deploying production systems
- Deep technical expertise in machine learning, including supervised/unsupervised learning, NLP, and/or deep learning
- Experience with large language models (LLMs), transformers, and modern NLP techniques (e.g., fine-tuning, embeddings, prompt engineering)
- Proven track record in designing, scaling, and maintaining ML systems in production (cloud-native solutions preferred – e.g., Azure, AWS, GCP)
- Excellent problem-solving skills and a passion for innovation and continuous learning
- Strong Python programming skills to write clean, modular code and experience with core data science libraries
- Solid software engineering practices: version control, modular design, unit/integration testing, CI/CD pipelines
- Comfortable working with both structured and unstructured data; experience writing with SQL queries
To be a successful Insurwaver, your attitude is as important. Insurwavers, like to Think Big, building with ambition, they put Client’s experience first and are incredible Team Players, who have each other\’s back. These are our Values which drive our Culture, personified by our Leadership Team and is key to what we are looking for in you.
Interview steps
- Preliminary phone call with the People Team (no video required)
- First video interview with our People Experience Manager
- Final interview with the hiring panel,
- Don’t be alarmed if there are other stages in the process, such as technical code tests, it’s all part of the plan for some of our roles.
What is Insurwave?
Insurwave is a disruptive Insurtech company leveraging the power of AI to consolidate and visualise data, helping clients to understand risk and make smarter risk transfer and insurance decisions.
Our platform offers an integrated insurance management experience, from ai-driven data ingestion through to collecting and consolidating risk data providing insight on business exposure changes in real-time.
What’s in it for me?
You’ll be part of a supportive team, working in a Values led culture, doing the exciting work that you thrive on, making a real difference and having the impact you know you can have. As well as incredible job satisfaction, you’ll also get:
- Lots of Holidays !: 25 days annual leave | 8 Bank Holidays
- More than a competitive salary: Private Health Care – Critical Illness Insurance – Life Insurance – 5% pension plan matching – cycle to work scheme
- Great work-life balance – Flexible working options
- A commitment to learning & development opportunities to support you in realising your potential
Altogether this makes Insurwave a fabulous place to work with incredible, friendly and supportive people!
Seniority level
-
Seniority level
Mid-Senior level
Employment type
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Employment type
Full-time
Job function
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Job function
Production, Analyst, and Information Technology
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Industries
Insurance, Technology, Information and Media, and Data Infrastructure and Analytics
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Contact Detail:
Insurwave Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning and AI, especially focusing on large language models and deep learning techniques. This will not only help you during interviews but also demonstrate your passion for continuous learning, which is highly valued at Insurwave.
✨Tip Number 2
Engage with the data science community by participating in forums, attending webinars, or contributing to open-source projects. This can provide you with insights into current trends and challenges in the field, making you a more attractive candidate.
✨Tip Number 3
Prepare to discuss your previous projects in detail, particularly those involving production systems and cloud-native solutions. Be ready to explain your problem-solving approach and how you’ve implemented best practices in MLOps.
✨Tip Number 4
Practice articulating your thoughts clearly and confidently, as communication is key in cross-functional teams. Consider mock interviews with peers to refine your ability to explain complex concepts in an accessible way.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and machine learning. Focus on projects where you've built and deployed production systems, especially those involving deep learning or NLP.
Craft a Compelling Cover Letter: In your cover letter, express your passion for innovation and continuous learning. Mention specific examples of how you've contributed to machine learning initiatives and your approach to problem-solving.
Showcase Technical Skills: Clearly outline your technical expertise in machine learning, including any experience with large language models and cloud-native solutions. Use bullet points to make this information easy to read.
Prepare for Interviews: Anticipate questions related to your experience with ML systems and be ready to discuss your problem-solving strategies. Consider preparing examples of past projects that demonstrate your skills and teamwork.
How to prepare for a job interview at Insurwave
✨Showcase Your Technical Expertise
As a Senior Data Scientist, it's crucial to demonstrate your deep understanding of machine learning concepts. Be prepared to discuss your experience with supervised and unsupervised learning, NLP, and deep learning techniques. Highlight specific projects where you've successfully implemented these skills.
✨Prepare for Technical Challenges
Expect technical assessments during the interview process. Brush up on your coding skills, particularly in Python, and be ready to solve problems on the spot. Familiarise yourself with core data science libraries and be prepared to discuss your approach to building production-grade ML systems.
✨Emphasise Collaboration and Teamwork
Insurwave values team players who can work collaboratively across functions. Share examples of how you've successfully collaborated with cross-functional teams in the past, and be ready to discuss how you can contribute to their team culture.
✨Demonstrate a Passion for Learning
The company is looking for candidates who are eager to learn and innovate. Talk about any recent trends or technologies in AI and data science that excite you, and how you plan to stay updated in this rapidly evolving field.
