At a Glance
- Tasks: Develop algorithms and work with cutting-edge AI/ML technologies in finance.
- Company: Join a leading financial tech firm in the heart of London.
- Benefits: Competitive salary, flexible working hours, and opportunities for growth.
- Other info: Collaborate globally and enhance your skills in a dynamic environment.
- Why this job: Dive into the fast-paced world of trading and make an impact with your coding skills.
- Qualifications: 1-3 years in C++, Python, and a passion for finance.
The predicted salary is between 35000 - 45000 £ per year.
Required Skills & Qualifications:
- 1–3 years of professional experience writing clean, preferably in modern C++, with a strong grasp of memory management and multi-threading.
- AI/ML Familiarity: Academic or professional experience working with machine learning libraries and frameworks.
- Interest in trading and financial markets.
- Ability to work in a fast-paced environment and with colleagues around the world.
- Quick to learn and curious about all things.
- Understand performance verification and optimization tools.
- CS Fundamentals: Strong understanding of object-oriented programming, data structures, and algorithmic complexity.
- Scripting & Data: Competence in Python, Perl, Shell scripting and SQL for data analysis, prototyping, and integrating AI models.
- Education: Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Mathematics, or a highly quantitative field.
Preferred Qualifications:
- Experience with networking protocols (TCP/IP, UDP) or hardware acceleration (CUDA/GPUs).
- Familiarity with CVS, git and Linux/Unix environments.
- Basic understanding of quantitative finance and algorithmic trading.
Junior Algorithmic Developer, Analyst, London employer: Jefferies Financial Group
As a Junior Algorithmic Developer in London, you will thrive in a dynamic and innovative environment that champions collaboration and continuous learning. Our company offers competitive benefits, a supportive work culture, and ample opportunities for professional growth, making it an ideal place for those passionate about technology and finance. Join us to be part of a forward-thinking team that values your contributions and encourages exploration in the exciting world of algorithmic trading.
StudySmarter Expert Advice🤫
We think this is how you could land Junior Algorithmic Developer, Analyst, London
✨Embrace Online Competitions
Get involved in online data science competitions like Kaggle or DrivenData. These platforms not only let you showcase your skills but also help you build a portfolio that stands out to hiring companies like Jefferies Financial Group when you're aiming for that entry-level role.
✨Join Data Science Meetups
Look for local data science meetups or workshops happening in your area. These are perfect for connecting with industry professionals and fellow newbies, giving us the chance to learn the ropes and get our foot in the door at companies like Jefferies Financial Group.
✨Networking Through University Career Services
Don't forget to leverage your university's career services! They often have exclusive internships and networking events specifically for entry-level data science positions. This is a golden opportunity to meet recruiters from companies like Jefferies Financial Group.
✨Spotlight Your Skills Online
Create a strong online presence by sharing your projects and insights on platforms like GitHub or LinkedIn. Make sure to apply directly through Jefferies Financial Group’s career page, where your unique skills can shine in their entry-level data science openings!
We think you need these skills to ace Junior Algorithmic Developer, Analyst, London
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at Jefferies Financial Group, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at Jefferies Financial Group aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.
How to prepare for a job interview at Jefferies Financial Group
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
