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- Tasks: Lead data science projects, collaborate with global teams, and communicate insights effectively.
- Company: Join a growing global data science firm focused on financial services across multiple markets.
- Benefits: Enjoy remote work flexibility and a commitment to diversity and inclusion.
- Why this job: Be part of an innovative team making impactful decisions in a dynamic industry.
- Qualifications: 8+ years of experience in data science, preferably in financial services, with strong technical skills.
- Other info: Fluency in French or German is a bonus; open to diverse applicants.
The predicted salary is between 51000 - 119000 £ per year.
Salary: £85,000 UK-Based (Remote)
I’m working with a global, growing data science capability which works across multiple markets. The team is distributed, and they are building on regional depth in Europe, with recent expansion into France and potential future moves into Germany.
Role: I’m looking for a seasoned data scientist (8+ years) with strong domain expertise in financial services, ideally someone who has worked across both B2B client-facing engagements. You’ll be working as part of a globally distributed team, collaborating with specialists across time zones. The right candidate would bring technical depth, business context, and the ability to communicate insights with both clients and internal teams.
Tech: While they use a range of technologies internally, familiarity with open-source tools is highly valued.
- Languages & Libraries: Python, R, Pandas, NumPy, scikit-learn, XGBoost, LightGBM, statsmodels
- NLP & ML Frameworks: spaCy, Hugging Face Transformers, TensorFlow or PyTorch (where applicable)
- Data Engineering & Pipelines: dbt, Airflow, SQL, Spark, Dask
- Visualisation: Plotly, Seaborn, Matplotlib, Dash, Streamlit
- Dev & Collaboration Tools: Jupyter, Git, Docker, VS Code, CI/CD tools
Ideal but Not Required: Fluency in French or German is a strong bonus as it will be advantageous for future client engagements. They are based in the UK with settled status, and comfortable working across time zones with colleagues in the US and South Asia.
If this sounds like something you are interested in, please get in contact: thomas.deakin@spgresourcing.com
SPG Resourcing is an equal opportunities employer and is committed to fostering an inclusive workplace which values and benefits from the diversity of the workforce we hire. We offer reasonable accommodation at every stage of the application and interview process.
Lead Data Scientist employer: SPG Resourcing
Contact Detail:
SPG Resourcing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist
✨Tip Number 1
Make sure to showcase your experience in financial services during any discussions. Highlight specific projects where you've successfully applied data science techniques to solve business problems, especially in B2B contexts.
✨Tip Number 2
Familiarise yourself with the technologies mentioned in the job description. Be prepared to discuss how you've used Python, R, and relevant libraries in your previous roles, as well as any experience with data engineering tools like dbt or Airflow.
✨Tip Number 3
Since the role involves collaboration across time zones, emphasise your ability to work in distributed teams. Share examples of how you've effectively communicated insights to both technical and non-technical stakeholders in past positions.
✨Tip Number 4
If you have any knowledge of French or German, make sure to mention it! Even if it's not a requirement, it could set you apart from other candidates and show your willingness to engage with clients in their native languages.
We think you need these skills to ace Lead Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your 8+ years of experience in data science, particularly in financial services. Emphasise any B2B client-facing roles and relevant technologies you've worked with, such as Python, R, and machine learning frameworks.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your technical skills and business acumen make you a great fit for the globally distributed team, and mention any language skills that could benefit future client engagements.
Showcase Relevant Projects: Include specific examples of projects where you've used the required technologies and frameworks. Highlight your contributions to these projects and the impact they had on the business or clients, especially in a remote or distributed setting.
Proofread and Edit: Before submitting your application, carefully proofread your documents for any spelling or grammatical errors. Ensure that your writing is clear and professional, as this reflects your attention to detail and communication skills.
How to prepare for a job interview at SPG Resourcing
✨Showcase Your Technical Skills
As a Lead Data Scientist, you'll need to demonstrate your expertise in Python, R, and various libraries like Pandas and scikit-learn. Be prepared to discuss specific projects where you've applied these technologies and the impact they had on your previous roles.
✨Communicate Clearly
Since you'll be collaborating with teams across different time zones, effective communication is key. Practice explaining complex data science concepts in simple terms, as you may need to present insights to clients who might not have a technical background.
✨Highlight Your Domain Expertise
With a focus on financial services, make sure to share relevant experiences that showcase your understanding of this sector. Discuss any B2B client-facing engagements you've had and how you navigated challenges in those situations.
✨Emphasise Adaptability and Collaboration
Working in a globally distributed team requires flexibility and teamwork. Share examples of how you've successfully collaborated with colleagues from different regions or cultures, and how you adapted to varying work styles and time zones.
