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- Tasks: Transform complex datasets into actionable insights using AI and machine learning.
- Company: Join a leading financial institution with a focus on innovation and analytics.
- Benefits: Flexible working, career development, and a collaborative team culture.
- Other info: Opportunities for growth in a globally recognised organisation.
- Why this job: Shape business strategy with high-visibility projects in a digital transformation environment.
- Qualifications: Strong Python skills, experience with large datasets, and knowledge of machine learning.
The predicted salary is between 60000 - 80000 £ per year.
We are currently partnering with a leading financial institution to recruit an experienced Senior Data Scientist to join a high-impact analytics and innovation team. This is a fantastic opportunity for a data professional who is passionate about using advanced analytics, AI, and machine learning to influence strategic decision-making at scale.
As a Senior Data Scientist, you will play a key role in transforming complex and high-volume datasets into meaningful, actionable insights that directly support business growth, innovation, and competitive advantage. This role offers exposure to cutting-edge data science initiatives, alongside the chance to influence long-term strategy within one of the UK’s most established financial services organisations.
- Design, develop, and deploy statistical and machine learning models to solve business problems
- Apply AI and advanced analytics techniques to enhance decision-making and operational efficiency
- Write high-quality, production-ready Python code and contribute to shared analytics codebases
- Query and manipulate large datasets using SQL and PySpark in distributed data environments
- Ensure strong governance, risk, and control standards are embedded in all analytical work
- Strong background in statistical analysis and modelling
- Advanced programming skills in Python
- Experience working with large datasets using SQL and/or PySpark
- Advanced knowledge of machine learning and AI techniques
- Experience within financial services or strong understanding of banking products, risk frameworks, and regulation
- Data visualisation skills, with the ability to present complex insights clearly and effectively
You may also be assessed on broader competencies such as risk and controls, business acumen, strategic thinking, change and transformation, and digital and technology capability.
Join a globally recognised financial institution undergoing significant digital and data transformation. Work on high-visibility projects that directly shape business strategy. Access long-term career development and progression opportunities. Flexible location options across London, Glasgow, or Northampton. Hybrid working model and supportive, collaborative team culture.
If you’re an experienced Data Scientist looking to take the next step in your career within a prestigious and forward-thinking organisation, we’d love to hear from you.
Data Science Data Science Senior Data Scientist (Python) (Remote) in London employer: Marshall Wolfe
Contact Detail:
Marshall Wolfe Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Data Science Senior Data Scientist (Python) (Remote) in London
✨Tip Number 1
Network like a pro! Reach out to connections in the financial services sector, especially those who work with data science. A friendly chat can lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving Python, SQL, and machine learning. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with large datasets and how you've applied AI in past roles. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Data Science Data Science Senior Data Scientist (Python) (Remote) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with Python, SQL, and machine learning techniques. We want to see how your skills align with the job description!
Showcase Your Projects: Include specific examples of projects where you've transformed complex datasets into actionable insights. We love seeing how you've applied advanced analytics in real-world scenarios, especially in financial services.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're passionate about data science and how you can contribute to our team. Be sure to mention your understanding of banking products and risk frameworks, as this will set you apart!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Marshall Wolfe
✨Know Your Data Science Stuff
Make sure you brush up on your statistical analysis and machine learning techniques. Be ready to discuss how you've applied these skills in real-world scenarios, especially in financial services. Prepare examples of models you've developed and the impact they had on decision-making.
✨Show Off Your Python Skills
Since this role requires advanced programming in Python, be prepared to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice writing clean, production-ready code. Familiarise yourself with common libraries used in data science, like Pandas and Scikit-learn.
✨Get Comfortable with SQL and PySpark
As you'll be working with large datasets, make sure you can query and manipulate data efficiently. Brush up on your SQL skills and understand how to use PySpark for distributed data processing. Be ready to discuss specific projects where you've used these tools.
✨Communicate Complex Insights Clearly
Data visualisation is key in this role, so think about how you can present complex insights in a straightforward way. Prepare to discuss how you've communicated findings to non-technical stakeholders in the past. Practising your storytelling skills will help you shine during the interview.