At a Glance
- Tasks: Design and develop AI/ML solutions to tackle real-world financial challenges.
- Company: Join a leading financial services firm in the heart of London.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative team environment with exciting projects in RegTech and FinCrime.
- Why this job: Make an impact in finance using cutting-edge AI and ML technologies.
- Qualifications: Experience in Python, SQL, and machine learning techniques required.
The predicted salary is between 60000 - 80000 £ per year.
We are looking for a data scientist to work with Financial services in London, UK.
Looking for talented and experienced data scientists with experience to join the programme. Solid knowledge and experience of AI and ML is essential.
- Design and develop AI / ML based solutions
- Work with other data scientists to build and deploy production-level solutions
- Troubleshoot and debug code
- Work with other teams to understand and solve business problems
Required Skills:
- Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and feature engineering
- SQL: For querying structured data sources
- Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models
- Machine Learning Deployment: Familiarity with containerised deployment (e.g. Podman, SageMaker, DSW pipelines)
- Version Control (Git): To maintain reproducible and collaborative workflows
- Time-Series Analysis: To assess risk trends over financial years
- Exploratory Data Analysis (EDA): To spot early signals or risk clusters
- Rank Aggregation/Ensemble Techniques: Understanding methods like Robust Rank Fusion (RRF)
- Model Explainability Tools: e.g. SHAP, LIME to support interpretability
- Experience with Model Monitoring & Drift Detection
- Experience in RegTech / FinCrime / Data-led Supervision Projects is a plus
- Experience developing solutions for record linkage and/or network analytics tasks
- Experience with graph query languages (e.g., Gremlin, Cypher), graph database platforms (e.g., Neptune, Neo4j), and/or graph visualisation platforms
Data Scientist - Financial services in London employer: Vallum Associates
Join a forward-thinking financial services firm in London, where innovation meets collaboration. As a Data Scientist, you'll thrive in a dynamic work culture that prioritises employee growth and development, offering access to cutting-edge AI and ML technologies. With a commitment to meaningful projects and a supportive team environment, this role provides an exceptional opportunity to make a significant impact in the financial sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Financial services in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Vallum Associates!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Scientist - Financial services at Vallum Associates.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Vallum Associates.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist - Financial services at Vallum Associates, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Scientist - Financial services in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Vallum Associates, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Vallum Associates. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Vallum Associates
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Vallum Associates!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
