At a Glance
- Tasks: Shape data science capabilities and tackle complex business problems with predictive models.
- Company: Join a leading consumer-facing business transforming its data platform.
- Benefits: Competitive salary, hybrid work, mentorship opportunities, and impactful projects.
- Other info: Collaborate with cross-functional teams and enjoy genuine leadership opportunities.
- Why this job: Make a real impact during a major data transformation and influence future practices.
- Qualifications: Degree in relevant field and 4+ years of data science experience required.
The predicted salary is between 90000 - 90000 £ per year.
Salary up to £90,000 + Benefits
Hybrid | London
We're working with a large, consumer-facing business undergoing a significant data platform transformation. Their Digital and Data division is moving away from a fragmented legacy estate towards a modern, governed platform built for scale. The Senior Data Scientist joining now will shape how that capability is built. You'll be setting the technical direction for modelling, owning the most complex problems, and connecting business outcomes to what actually gets built.
Responsibilities as a Senior Data Scientist:
- Build and deploy predictive models and advanced analytics solutions for high-value use cases
- Define the features, datasets and structures required for modelling, working closely with the Lead Data Modeller and Data Engineering teams
- Translate business problems into clear analytical approaches, challenging poorly defined requests and driving clarity on outcomes
- Communicate trade-offs between model complexity, data availability, and delivery timelines to senior stakeholders
- Establish and enforce best practices for modelling, evaluation, and production deployment
- Implement peer review processes across model and code quality
- Mentor junior and mid-level Data Scientists and contribute to capability development across the team
- Partner with Data Engineers to ensure model readiness and operational deployment
Requirements:
- Degree in Computer Science, Mathematics, Engineering or a related field
- At least 4 years of experience in a data science or statistical role with a track record of delivering impactful solutions
- Proven experience developing and deploying machine learning models and statistical analysis
- Strong proficiency in Python and SQL, with experience in Spark SQL
- Familiarity with cloud platforms and distributed computing tools such as Azure Synapse, Snowflake, or Databricks
- Ability to work with large datasets and complex data structures
- Strong background in applying statistical and machine learning techniques to solve real business problems
- Clear communication skills, including the ability to explain technical concepts to non-technical stakeholders
Why apply?
- Join at a pivotal moment in a major platform transformation, with real influence over how data science is structured and practised
- Work across a dual-mode environment that balances maintaining a live estate with building something new
- Genuine scope for mentorship and leadership without a management overhead
- Cross-functional collaboration with Lead Data Modellers, Data Engineers, and senior business stakeholders
- A business with the scale and data complexity to keep a strong Senior Data Scientist genuinely challenged
If you're a Senior Data Scientist who wants to define the work rather than just execute it, we'd like to hear from you. Apply below or get in touch directly to find out more.
Please note: due to the volume of applications we receive, we may not be able to respond to every applicant individually. If you haven't heard from us within two weeks, please assume your application has not been successful on this occasion.
Senior Data Scientist in City of London employer: Formula.
Join a leading consumer-facing business in London that is at the forefront of a transformative data platform journey. As a Senior Data Scientist, you'll enjoy a collaborative work culture that values mentorship and innovation, with ample opportunities for professional growth while tackling complex data challenges. With a competitive salary and benefits, this role offers a unique chance to shape the future of data science within a dynamic environment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist in City of London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Formula.!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Scientist at Formula..
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Formula..
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Scientist at Formula., make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Scientist in City of London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Formula., your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Formula.. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Formula.
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Formula.!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
