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- Tasks: Transform real-world problems into data-driven solutions and deploy machine learning models.
- Company: Established financial services organisation with a growing data and AI capability.
- Benefits: Competitive salary, bonus, and clear progression towards leadership roles.
- Why this job: Make a meaningful impact while mentoring others in a collaborative environment.
- Qualifications: Experience as a Data Scientist with strong Python skills and model deployment experience.
- Other info: Opportunity to influence processes in a supportive data function.
The predicted salary is between 48000 - 72000 £ per year.
We are supporting a well established financial services organisation that is growing its data and AI capability and looking to hire an experienced Data Scientist at senior level. This is a hands on role with a clear path into leadership over the next one to two years.
You will join a high calibre data science team that owns the full lifecycle of its work from problem definition through to deploying and monitoring models in production. The environment is collaborative with strong visibility across the business and regular exposure to senior stakeholders.
The role:
- Work closely with product technology and business stakeholders to turn real commercial problems into data driven solutions.
- Design, build and deploy machine learning models into production environments.
- Own models post deployment including performance monitoring and iteration.
- Communicate insights and impact clearly to non-technical audiences.
- Mentor junior data scientists and contribute to technical standards and best practice.
- Operate in an environment with strong governance, quality and engineering principles.
What we are looking for:
- Solid experience as a Data Scientist working on applied commercial problems.
- Strong Python skills and experience with common machine learning libraries.
- Experience deploying models into production rather than purely experimentation.
- Exposure to cloud platforms such as Azure, AWS or GCP.
- Confidence working with stakeholders and explaining the impact of your work.
- An interest in growing into a lead role while remaining hands on.
- Experience in regulated environments or financial services is helpful but not essential.
Why apply:
- Clear progression toward a lead level role.
- Ownership of meaningful work with visible business impact.
- Strong supportive data function with room to influence how things are done.
- Competitive salary and bonus with transparency throughout the process.
Senior Data Scientist in London employer: Sanderson
Contact Detail:
Sanderson Recruiting Team
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 current employees in the company you're eyeing, especially those in data roles. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your best projects, especially those involving machine learning models. Being able to discuss your hands-on experience will set you apart from the crowd.
✨Tip Number 3
Practice your pitch! Be ready to explain complex data concepts in simple terms. This is key when communicating with non-technical stakeholders, so make sure you can showcase your insights clearly.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step!
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 speaks directly to the role of Senior Data Scientist. Highlight your experience with machine learning models, Python skills, and any relevant projects that showcase your ability to solve commercial problems.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've turned data into actionable insights and how you’ve collaborated with stakeholders in the past.
Showcase Your Technical Skills: Don’t just list your skills; demonstrate them! Mention specific machine learning libraries you’ve used and any cloud platforms you’re familiar with. We want to see how you’ve applied these in real-world scenarios.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Sanderson
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around machine learning models and their deployment. Be ready to discuss specific projects where you've turned commercial problems into data-driven solutions, as this will show your hands-on experience.
✨Showcase Your Python Skills
Since strong Python skills are a must, prepare to demonstrate your proficiency. You might be asked to solve a problem on the spot or explain how you've used libraries like TensorFlow or Scikit-learn in your previous work. Have examples ready!
✨Communicate Like a Pro
You’ll need to explain complex concepts to non-technical stakeholders, so practice simplifying your insights. Think of ways to present your past work and its impact clearly and concisely, as this will highlight your ability to bridge the gap between data science and business.
✨Be Ready to Lead
Since there's a clear path to leadership, express your interest in mentoring junior data scientists and contributing to best practices. Share any experiences where you've taken initiative or led a project, as this will show you're ready for the next step.
