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, 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 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 employer: Primis
This boutique financial consulting firm in London is an exceptional employer, offering a collaborative culture that fosters innovation and professional growth. Employees benefit from engaging in high-impact projects with leading financial institutions, while also enjoying opportunities for mentorship and skill development in a supportive environment. With a focus on diversity and inclusion, the firm actively encourages underrepresented talent to apply, ensuring a rich and varied workplace experience.
StudySmarter Expert Advice🤫
We think this is how you could land Marketing Data 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 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 discussing your experience and problem-solving skills, the better your chances of impressing the interviewers.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting opportunities waiting for talented individuals like you. Plus, applying directly shows your enthusiasm and commitment to joining our team.
We think you need these skills to ace Marketing Data Scientist
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-impact work.
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 don’t miss out on any important updates. Plus, we’re excited to see what you bring to the table!
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 teamwork is key in this 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 during the interview.
✨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 and helps you assess if the company is the right fit for you.
