At a Glance
- Tasks: Lead data science projects and deliver machine learning solutions in finance.
- 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 solutions and impactful projects.
- 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.
Data Marketing Scientist 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 Data Marketing Scientist, you'll enjoy opportunities for professional growth while tackling complex data science challenges, all within a supportive environment that values diversity and encourages underrepresented talent to thrive.
StudySmarter Expert Advice🤫
We think this is how you could land Data Marketing Scientist
✨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
Show off your skills! Create a portfolio showcasing your machine learning projects and data science solutions. This is your chance to demonstrate your expertise and creativity, so make sure it’s easily accessible when you’re chatting with potential employers.
✨Tip Number 3
Prepare for those interviews! Research the company and their projects, and be ready to discuss how your experience aligns with their needs. We recommend practising common interview questions and even some technical challenges to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented individuals like you. Plus, applying directly can sometimes give you an edge over other candidates, so don’t miss out!
We think you need these skills to ace Data Marketing Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the job description. Highlight your experience with machine learning, Python, and any cloud platforms you've worked with. We want to see how your skills align with the role!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data science and how you’ve tackled complex challenges in the past. Let us know why you’re excited about this opportunity and how you can contribute to our team.
Showcase Your Projects:If you’ve got any projects that demonstrate your ability to build and ship production-ready solutions, don’t hold back! Include links or descriptions of your work, especially if it involves machine learning models or data engineering.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
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 tools. Be ready to discuss your experience with Python, cloud platforms like Azure or AWS, and any MLOps practices you've used. The more specific examples you can provide about your past projects, the better!
✨Showcase Your Collaboration Skills
Since this role involves working closely with engineers and business stakeholders, be prepared to talk about how you've successfully collaborated in the past. Share examples of how you bridged gaps between technical solutions and commercial goals, as this will highlight your ability to work in a team-oriented environment.
✨Prepare for Technical Questions
Expect some technical questions that test your knowledge of model tuning and system design. Practise explaining your thought process when building and deploying models, and be ready to tackle hypothetical scenarios that might come up in the financial services sector.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team dynamics, the types of projects you'll be working on, and how success is measured in this role. This shows your genuine interest in the position and helps you determine if it's the right fit for you.
