At a Glance
- Tasks: Elevate statistical modelling capabilities and build scalable solutions for clients.
- Company: AI-native consultancy with a global client base and strong market momentum.
- Benefits: Competitive salary of £80,000 plus package, hybrid work model, and career growth.
- Other info: Mentorship opportunities and a dynamic, collaborative work environment.
- Why this job: Make a real impact in data transformation across complex industries.
- Qualifications: Strong background in statistics/biostatistics and advanced R experience.
The predicted salary is between 80000 - 80000 £ per year.
I’m working with a growing, AI-native consultancy who are continuing to scale following a recent acquisition, giving them strong backing, a global client base, and real momentum in the market. They deliver high-impact data and digital transformation work across complex, highly regulated industries, and are now looking to bring in a Senior Data Scientist with a strong statistical / biostatistics background.
This role is focused on helping clients elevate their statistical modelling capabilities taking models from research-grade through to production-ready, scalable solutions. You’ll work closely with client-side biostatisticians and technical teams, acting as a subject matter expert, helping to modernise ways of working and embed best practices across modelling and engineering.
Key responsibilities include:- Designing and improving statistical modelling approaches alongside client teams
- Building scalable, production-ready workflows using R
- Supporting the deployment of models into cloud-based environments
- Implementing best practices across CI/CD, testing, and documentation
- Ensuring models are reproducible, maintainable, and performant
- Acting as a technical advisor to stakeholders, translating complex concepts into practical solutions
- Mentoring teams and improving overall modelling and engineering standards
- Strong background in statistics or biostatistics
- Advanced experience with R, including package development
- Experience working with version control (Git) and collaborative workflows
- Good understanding of CI/CD pipelines, testing, and documentation practices
- Experience deploying models or analytical workflows into production environments
- Exposure to cloud platforms such as Databricks, AWS, or Azure
- Strong communication skills with the ability to work in a client-facing / advisory capacity
Senior Data Scientist in London employer: develop
Join a dynamic and innovative AI-native consultancy in London, where your expertise as a Senior Data Scientist will be valued and nurtured. With a strong focus on employee growth, you will have the opportunity to work on high-impact projects in a collaborative hybrid environment, benefiting from a competitive salary and comprehensive package. The company fosters a culture of continuous learning and mentorship, ensuring that you can elevate your skills while contributing to transformative data solutions for a global client base.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who work in biostatistics. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your statistical modelling projects and any R packages you've developed. 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. Be ready to discuss how you've implemented CI/CD practices and worked with cloud platforms like AWS or Azure in past projects.
✨Tip Number 4
Don't forget to apply through our website! We have loads of opportunities that might be perfect for you. Plus, it’s a great way to get noticed by our hiring team directly.
We think you need these skills to ace Senior Data Scientist in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in statistics and biostatistics, especially with R. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about this role and how your background makes you the perfect fit. Remember, we love seeing your personality come through!
Showcase Your Technical Skills:Since this role involves deploying models and working with cloud platforms, make sure to mention any experience you have with CI/CD, Git, and cloud services like AWS or Azure. We’re keen to see how you can contribute to our tech stack!
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 develop
✨Know Your Stats
Brush up on your statistical and biostatistical knowledge. Be ready to discuss specific models you've worked on, how you approached them, and the outcomes. This role is all about elevating statistical modelling capabilities, so showing your expertise will definitely impress.
✨Showcase Your R Skills
Since advanced experience with R is crucial, prepare to demonstrate your proficiency. Bring examples of package development or workflows you've built. If possible, share a project where you successfully deployed a model into a cloud environment, as this will highlight your practical skills.
✨Understand CI/CD Practices
Familiarise yourself with CI/CD pipelines and best practices in testing and documentation. Be prepared to discuss how you've implemented these in past projects. This shows that you not only understand the theory but can also apply it effectively in real-world scenarios.
✨Communicate Clearly
As this role involves acting as a technical advisor, practice translating complex concepts into simple terms. Think of examples where you've had to explain technical details to non-technical stakeholders. Strong communication skills are key, so make sure you convey your ideas clearly and confidently.
