At a Glance
- Tasks: Lead data science projects and deliver machine learning solutions for financial services.
- Company: Boutique financial consulting firm with a collaborative culture.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Encouraging diverse talent to apply and supporting accessibility needs.
- Why this job: Shape the future of data science in finance and tackle real-world challenges.
- 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 scientist (marketing) 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 Scientist, you'll enjoy the opportunity to take ownership of complex data challenges while benefiting from a supportive environment that fosters professional growth and innovation. With a focus on meaningful projects and a commitment to diversity, this is an excellent place for those looking to make a significant impact in the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data scientist (marketing)
✨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 data science projects, especially those involving machine learning solutions. We want to see your work in action, so make sure it’s easily accessible and highlights your problem-solving abilities.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you’ll need to communicate effectively with both technical and non-technical stakeholders. We’re all about collaboration here!
✨Tip Number 4
Don’t hesitate to apply through our website! Even if you don’t tick every box, we encourage everyone to throw their hat in the ring. Your unique perspective could be just what we need to enhance our high-performing team.
We think you need these skills to ace Data scientist (marketing)
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 skills in building and deploying machine learning models, don’t hold back! Include links or descriptions of your work to give us a taste of what you can do.
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’ve bridged the gap between technical solutions and commercial goals.
✨Prepare for Technical Questions
Expect some technical questions that test your knowledge of model tuning and system design. Practise explaining complex concepts in simple terms, as you might need to communicate these ideas to non-technical team members.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team’s current projects, the challenges they face, or how they measure success. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
