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For Companies At a Glance
- Tasks: Support Portfolio Managers by analysing data to inform trading decisions.
- Company: Join a prestigious systematic trading firm known for its innovative approach.
- Benefits: Enjoy competitive pay, opportunities for growth, and a dynamic work environment.
- Why this job: Be part of an industry leader and make impactful contributions in finance.
- Qualifications: PhD in Computer Science, Maths, Physics or related field; strong Python skills required.
- Other info: Experience with large data sets and predictive modelling is essential.
The predicted salary is between 43200 - 72000 £ per year.
Job title: Senior Data Scientist (Trading)
Location: London (Canary Wharf) – 3 days onsite per week (non-negotiable)
Rate: £700 per day (Inside IR35)
Length: Initial 6 months (strong likelihood of extension)
Summary
An immediate requirement for multiple Senior Data Scientists to support a large-scale trading environment within a complex, data-driven organisation. The role focuses on building and deploying scalable data science and machine learning solutions that deliver tangible business value. This is a hands-on position suited to experienced practitioners with strong engineering, statistical, and communication skills.
Responsibilities
- Design, develop, and productionise scalable data science and machine learning products
- Collaborate closely with data engineers, software engineers, and business stakeholders
- Apply strong statistical and machine learning foundations to solve real-world trading problems
- Perform in-depth data analysis to generate actionable business insights
- Work across the full data lifecycle, from discovery and prototyping through to deployment and maintenance
- Contribute to GenAI / LLM-based use cases, explaining solutions to both technical and non-technical audiences
- Write clean, well-documented, and testable code in complex environments
- Engage in technical discussions and reviews, maintaining a pragmatic and value-focused mindset
Desired Skills
- Strong development experience in Python and/or other object-oriented languages (e.g. Java)
- Excellent grounding in statistics, machine learning, and mathematical concepts
- Proven experience delivering production-grade data science solutions
- Hands-on experience with modern data science tooling, including LLMs / RAG approaches
- Advanced SQL skills
- Experience working in complex, enterprise-scale environments
- Strong written and verbal communication skills
- Ability to perform under technical interviews including live coding, OOP design, and SQL
Contact
Email: Harry@paritasrecruitment.com
Mobile (WhatsApp message):+44 7702 946 250
Data Scientist employer: Paritas Recruitment
Contact Detail:
Paritas Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Make sure to showcase your experience with large data sets during any networking opportunities. Engage in conversations with professionals in the trading or data science fields, and highlight specific projects where you've successfully applied classification, regression, or predictive modelling techniques.
✨Tip Number 2
Join relevant online communities or forums where data scientists and traders interact. This can help you gain insights into the industry and potentially connect with someone from the firm or similar firms who can provide valuable advice or even refer you for the position.
✨Tip Number 3
Attend industry conferences or meetups focused on data science and trading. These events are great for networking and can give you a chance to meet people from the firm directly, allowing you to express your interest and discuss your qualifications in person.
✨Tip Number 4
Consider creating a portfolio that showcases your Python skills and any relevant projects you've worked on. This could include visualisations, models, or analyses that demonstrate your ability to handle complex data tasks, making you stand out when you apply through our website.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your PhD in a relevant field and any commercial experience you have. Emphasise your strong Python skills and mention any additional programming languages you know, as well as your experience with large data sets.
Craft a Compelling Cover Letter: In your cover letter, explain why you're interested in the Data Scientist position at this trading firm. Discuss how your background in Computer Science, Maths, or Physics aligns with their needs and how your skills can support Portfolio Managers in making trading decisions.
Showcase Relevant Projects: If you've worked on projects involving classification, regression, distribution analysis, or predictive modelling, be sure to include these in your application. Provide specific examples of how you applied your skills to solve real-world problems.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors or typos. A polished application reflects your attention to detail, which is crucial in a data-driven role.
How to prepare for a job interview at Paritas Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python and any other programming languages you know. Bring examples of projects where you've used these skills, especially those involving large data sets and predictive modelling.
✨Demonstrate Your Analytical Thinking
Expect questions that assess your problem-solving abilities. Be ready to explain your thought process when tackling complex data analysis tasks, such as classification or regression problems.
✨Connect Your Experience to the Role
Highlight your commercial experience in similar environments. Discuss specific instances where your work has directly supported decision-making processes, particularly in trading or finance.
✨Prepare for Technical Challenges
You may face technical challenges or case studies during the interview. Practice coding problems and data analysis scenarios beforehand to demonstrate your ability to think on your feet and apply your knowledge effectively.
