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For Companies At a Glance
- Tasks: Design data pipelines and develop machine learning models for trading insights.
- Company: Global financial services firm focused on innovation in fixed income markets.
- Benefits: Earn up to £750 per day with a 6-month contract.
- Why this job: Join a fast-paced team and make an impact in electronic trading.
- Qualifications: Strong Python and SQL skills, with experience in data science and machine learning.
- Other info: Collaborative environment with opportunities to learn about finance and trading.
Collaborate with traders, quants, and technologists in a fast-paced environment.
About Our Client
Our client is a global financial services organisation with a strong presence in fixed income markets. They are committed to innovation and technology-driven trading solutions, offering a collaborative environment where data plays a critical role in decision-making.
Job Description
- Design and build data pipelines for real-time and historical trading data.
- Develop machine learning models for trade flow prediction, execution analysis, and market pattern recognition.
- Create dashboards and analytical tools for trading desks.
- Productionise models and integrate them into trading infrastructure.
- Ensure data quality, governance, and automation of analytical workflows.
- Collaborate with traders, quants, and technologists to identify data-driven opportunities.
The Successful Applicant
- Strong programming skills in Python (pandas, NumPy, scikit-learn) and SQL.
- Experience in data science, machine learning, and predictive modelling.
- Background in data engineering (ETL pipelines, streaming tech like Kafka).
- Familiarity with cloud platforms (AWS, Azure, GCP).
- Excellent communication skills for technical and non-technical stakeholders.
- Exposure to financial services or willingness to learn fixed income and electronic trading.
- Typically 3-7 years' experience in data science, analytics engineering, or software development.
What’s on Offer
- £750 per day INSIDE IR35
- 6 month contract
- Based in Liverpool Street - 4 days per week in the office
Data Scientist - Fixed Income Electronic Trading employer: Michael Page (UK)
Contact Detail:
Michael Page (UK) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Fixed Income Electronic Trading
✨Tip Number 1
Network like a pro! Reach out to your connections in the finance and tech sectors. Attend meetups or webinars related to data science and trading. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, machine learning models, and dashboards. 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 skills. Be ready to discuss your experience with Python, SQL, and cloud platforms. Practice explaining complex concepts in simple terms for non-technical stakeholders.
✨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 get noticed by hiring managers who are looking for talent like yours.
We think you need these skills to ace Data Scientist - Fixed Income Electronic Trading
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your programming skills in Python and SQL, as well as your experience with data science and machine learning. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the opportunity to work in fixed income electronic trading. We love seeing enthusiasm and a clear understanding of how data drives decision-making in this field.
Showcase Collaboration Skills: Since the role involves working closely with traders, quants, and technologists, make sure to mention any past experiences where you’ve successfully collaborated with diverse teams. We value communication skills, so highlight how you can bridge the gap between technical and non-technical stakeholders.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Michael Page (UK)
✨Know Your Tech Stack
Make sure you’re well-versed in Python, SQL, and any relevant libraries like pandas and NumPy. Brush up on your machine learning concepts and be ready to discuss how you've applied them in real-world scenarios.
✨Showcase Your Collaboration Skills
Since the role involves working with traders and quants, prepare examples of how you've successfully collaborated with different teams. Highlight your communication skills and how you’ve translated complex data insights for non-technical stakeholders.
✨Demonstrate Your Problem-Solving Ability
Be ready to tackle some technical questions or case studies during the interview. Think about how you would approach designing data pipelines or productionising models, and articulate your thought process clearly.
✨Research the Company and Market
Familiarise yourself with the client’s position in the fixed income market and their trading strategies. Showing that you understand their business and are eager to learn more about electronic trading will set you apart from other candidates.
