At a Glance
- Tasks: Lead data science projects and develop machine learning solutions for financial services.
- Company: Boutique financial consulting firm with a collaborative culture.
- Benefits: Competitive salary, inclusive environment, and opportunities for professional growth.
- Other info: Encouraging diverse talent to apply and supporting accessibility needs.
- Why this job: Shape the future of finance with innovative data science solutions.
- Qualifications: Experience in Python, machine learning, and cloud platforms like Azure or AWS.
The predicted salary is between 60000 - 80000 £ per year.
We're partnered with a boutique financial consulting firm seeking experienced Data Scientists to join their growing data practice in London. Known for their collaborative culture and high-impact work with leading financial institutions, this is a rare opportunity to take ownership of complex data science challenges while shaping the direction of a high-performing team.
You'll lead end-to-end delivery of machine learning solutions - from early proof-of-concept through to production - working alongside engineers, domain experts, and business stakeholders across the financial services sector.
- Taking ownership of data science projects from initial concept and rapid prototyping through to live production deployment.
- Building and iterating on machine learning models that address real-world business problems across financial services.
- Partnering with engineering, business, and domain teams to bridge the gap between commercial goals and technical solutions.
- Serving as the go-to expert on ML system design, model tuning, and bringing solutions to production at scale.
- Proven ability to build and ship production-ready data science solutions using Python and the wider ML ecosystem.
- Deep practical knowledge of applied machine learning, spanning model development through to data engineering.
- Comfortable working across major cloud platforms (Azure, AWS or GCP) with hands-on exposure to tools like Spark, Hive or Redshift.
- Experience with MLOps practices - CI/CD, model monitoring, DevOps integration.
We encourage underrepresented talent to apply to all our roles & support accessibility needs.
Marketing Data Scientist in London employer: Primis
Join a boutique financial consulting firm in London that champions a collaborative culture and offers high-impact work with leading financial institutions. As a Marketing Data Scientist, you'll enjoy a supportive environment that fosters professional growth, allowing you to take ownership of complex data science challenges while working alongside talented engineers and domain experts. With a focus on innovation and inclusivity, this firm not only values your contributions but also encourages diverse talent to thrive in their dynamic team.
StudySmarter Expert Advice🤫
We think this is how you could land Marketing Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for those interviews by practising common data science questions and case studies. We recommend doing mock interviews with friends or using online platforms. The more comfortable you are, the better you'll perform when it counts!
✨Tip Number 3
Show off your projects! Create a portfolio showcasing your machine learning models and data science projects. We love seeing real-world applications of your skills, so make sure to highlight how you've tackled complex problems in your previous roles.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you an edge over other candidates. So, what are you waiting for? Get your application in!
We think you need these skills to ace Marketing Data Scientist in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your experience with machine learning, Python, and any cloud platforms you've worked with. 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 aligns with the role. Don’t forget to mention your collaborative spirit and how you can contribute to our high-performing team.
Showcase Your Projects:If you've worked on relevant projects, make sure to include them in your application. Whether it's a personal project or something from your previous job, we love seeing real-world applications of your skills, especially in financial services.
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’re considered for the role. Plus, it shows us you’re keen on joining our awesome team!
How to prepare for a job interview at Primis
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning concepts and be ready to discuss your experience with Python and the ML ecosystem. Be prepared to share specific examples of projects you've worked on, especially those that involved building and deploying models in a production environment.
✨Understand the Business Context
Since this role involves bridging the gap between technical solutions and commercial goals, do your homework on the financial services sector. Familiarise yourself with common challenges faced by financial institutions and think about how your skills can address these issues.
✨Showcase Your Collaboration Skills
This position is all about teamwork, so be ready to talk about how you've successfully collaborated with engineers, domain experts, and business stakeholders in the past. Highlight any experiences where you took ownership of a project and led a team towards a successful outcome.
✨Get Comfortable with Cloud Platforms
Since the job requires working across major cloud platforms like Azure, AWS, or GCP, make sure you’re familiar with the tools and services offered by these platforms. If you have hands-on experience with Spark, Hive, or Redshift, be sure to mention it during the interview!
