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.
BI Data Modeler 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 BI Data Modeler, you'll enjoy a supportive environment that fosters professional growth, encourages innovation, and provides opportunities to lead complex data science projects from concept to production. With a focus on diversity and inclusion, this firm actively seeks to empower underrepresented talent, making it an excellent choice for those looking to make a meaningful impact in the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land BI Data Modeler in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at the firm you're eyeing. A friendly chat can open doors and give you insider info that could set you apart.
✨Tip Number 2
Showcase your skills! Prepare a portfolio of your best projects, especially those involving machine learning and data engineering. This will help you demonstrate your expertise and make a lasting impression during interviews.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions related to data science and machine learning. Mock interviews with friends or mentors can help you articulate your thoughts clearly and confidently.
✨Tip Number 4
Apply through our website! We want to see your application, so don’t hesitate to submit it directly. It shows initiative and gives us a chance to connect with you right away!
We think you need these skills to ace BI Data Modeler in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the BI Data Modeler role. 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 tell us why you're passionate about data science and how your background aligns with our collaborative culture. Don't forget to mention specific projects or achievements that showcase your expertise.
Showcase Your Projects:If you've worked on relevant data science 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. It helps us understand your approach to problem-solving!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It streamlines the process and ensures your application reaches the right people. Plus, it shows us you're serious about joining our 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 tools. Be ready to discuss your experience with Python, MLOps practices, and cloud platforms like Azure or AWS. They’ll want to see that you can not only talk the talk but also walk the walk when it comes to building and deploying models.
✨Showcase Your Collaboration Skills
Since this role involves working closely with engineers and business stakeholders, be prepared to share examples of how you've successfully collaborated in the past. Highlight any projects where you bridged the gap between technical solutions and commercial goals, as this will resonate well with the interviewers.
✨Prepare for Real-World Scenarios
Expect to tackle some practical problems during the interview. Think about how you would approach a data science challenge in the financial sector. Practising with case studies or real-world examples can help you articulate your thought process and problem-solving skills effectively.
✨Ask Insightful Questions
Interviews are a two-way street, so come armed with questions that show your interest in the company and the role. Ask about their current data projects, team dynamics, or how they measure success in their data practice. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
