At a Glance
- Tasks: Manage trading systems and optimise processes in a fast-paced environment.
- Company: Join a dynamic startup at the forefront of iGaming technology.
- Benefits: Competitive salary, performance bonuses, and opportunities for growth.
- Other info: Flexible shifts with potential for career advancement in a collaborative setting.
- Why this job: Be part of an innovative team and make a real impact in the betting industry.
- Qualifications: BSc in Mathematics or related field; strong work ethic and understanding of betting markets.
The predicted salary is between 36000 - 60000 £ per year.
About White Swan Data
Technology is at the heart of our business and has produced consistent and significant results. We are a small but rapidly growing team of mathematicians, data scientists and software engineers constantly striving to refine our world class statistical models while also researching and deploying new ones. Our work bridges three domains, each challenging in its own right - iGaming, quantitative research and software development. This convergence demands a rare blend of skills and creativity to identify and capitalise on inefficiencies across the iGaming landscape. The opportunities are vast, but we are only as good as the people we bring on board. As a startup, we offer a dynamic and entrepreneurial environment where you’ll work on impactful projects and have the autonomy to explore new ideas. In‑person collaboration and innovation are at the heart of what we do, and we are always looking for individuals who can contribute their unique perspectives and talents to help us stay ahead in a constantly evolving industry.
About the Role
Markets never sleep and at White Swan Data we are analysing markets 24/7, 365 days a year. We are expanding our execution team for Racing and Football. We are looking for high energy, curious people with an understanding of betting markets to join our in house fixed odds team. This role will require availability for day, evening, and weekend shifts. The successful applicant will have a love of data, with a growth mindset and proactive approach that will assist our administration team in achieving their targets. We are an ambitious company which means there is considerable opportunity for you to make a niche for yourself and to progress within the business.
Key Responsibilities
- Manage trading system to maximise volume of trades, hitting target metrics.
- Work closely with developers and quants to improve trading system with practical feedback.
- Work closely with the operational support team to optimise the trading pipeline.
- Solve practical problems quickly to minimise trading downtime.
Skills, Knowledge and Expertise
At White Swan Data, we like to give individuals responsibility from an early stage. Although you will receive monitoring, we like hungry and independent individuals, who are looking to improve in an agile and at times intense working environment.
- BSc in Mathematics or a similar discipline (physics, economics etc.)
- Strong work ethic, and desire to succeed.
- Track record of excellence within a technical field (not necessarily academic).
- Ability to act precisely to instruction and communicate technical issues clearly.
- Availability on weekends and evenings.
- You are able to balance a variety of tasks at once, managing your time proficiently.
- You are willing to work some unsociable hours (weekends, early mornings, and late nights).
- A good understanding of betting and odds will also be beneficial.
Benefits
- Salary depending on experience.
- Annual discretionary performance bonus.
Sports Trader employer: White Swan Data
White Swan Data is an excellent employer for those looking to thrive in the dynamic world of betting operations. With a competitive salary, performance bonuses, and a collaborative work culture, employees are encouraged to grow and develop their skills in a supportive environment. Located in London, the company offers unique opportunities to engage with a diverse team while honing your analytical abilities in a fast-paced industry.
StudySmarter Expert Advice🤫
We think this is how you could land Sports Trader
✨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 White Swan Data!
✨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 Sports Trader at White Swan Data.
✨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 White Swan Data.
✨Apply Directly through Our Website
When you find a suitable opening like Sports Trader at White Swan Data, 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 Sports Trader
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 White Swan Data, 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 White Swan Data. 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 White Swan Data
✨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 White Swan Data!
✨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.
