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- Tasks: Design and implement innovative machine learning models for sports betting analytics.
- Company: Join Longshot Systems, a cutting-edge company in sports betting technology.
- Benefits: Enjoy competitive salary, uncapped bonuses, private healthcare, and gym membership.
- Why this job: Make a real impact with your creativity in a dynamic R&D environment.
- Qualifications: PhD or research Masters in a quantitative subject and Python modelling experience.
- Other info: Flexible working hours and a supportive team culture await you.
The predicted salary is between 36000 - 60000 £ per year.
At Longshot Systems we're building advanced platforms for sports betting analytics and trading. We're hiring Graduate Machine Learning Researchers for our quantitative modelling team. The primary goal of this team is to improve the predictive power of our models based on historical event data. The quality of our models is incredibly important to us and improvements on our models directly impact company success.
You will design, test, and implement new machine learning models in Python, continually improving our existing state-of-the-art solutions. Longshot is a small, focused company and so the role suits someone who wants to be involved in all aspects of the R&D process, from high-level design through to production implementation and a keenness to learn from experienced industry experts.
The ideal candidate will be highly creative and enjoy generating new, innovative ways to tackle problems and suggesting improvements to existing methodologies; you'll have a high level of autonomy to research whichever methods you felt would be best suited to the problem at hand. A strong mathematical understanding of the fundamentals of Machine Learning and core statistics is very important for this role. Knowledge of sports betting isn't required.
We are a hybrid working company, working Thursdays in our London (Farringdon) office and remotely the rest of the week. Our typical working hours are 10 am to 6 pm UK time, Monday to Friday, but we support flexible working and trust our team to manage their own schedules to meet their goals.
Our interview process is as follows:
- Intro call (30 mins) - your background + interests
- Technical interview (60 mins) - modelling discussion + scenario questions
- Full assessment day (9:30-5pm) - solving a real modelling problem using near-production-level data
Requirements
- PhD or research Masters in a quantitative, technical subject (e.g. Maths, Physics, Machine Learning) from a top university
- Experience modelling tabular data in Python
Benefits
- Participation in the uncapped company bonus scheme, typically 10-20% of salary depending on experience
- 10% matched pension contributions
- Private healthcare insurance
- Long term illness insurance
- Gym membership
- Choose your own hardware & setup for your development environment
Graduate Machine Learning Researcher employer: Longshot Systems
Contact Detail:
Longshot Systems Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graduate Machine Learning Researcher
✨Tip Number 1
Get your networking game on! Connect with professionals in the machine learning and sports analytics fields. Attend meetups, webinars, or even just reach out on LinkedIn. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Prepare for those interviews like a pro! Brush up on your Python skills and be ready to discuss your modelling experiences. We recommend practising common technical questions and even doing mock interviews with friends or mentors to build your confidence.
✨Tip Number 3
Show off your passion for machine learning! When you get the chance to chat with potential employers, share your projects or any innovative ideas you have. We love seeing candidates who are genuinely excited about tackling real-world problems.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always looking for fresh talent who can bring new perspectives to our team.
We think you need these skills to ace Graduate Machine Learning Researcher
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Python and any machine learning models you've worked on. We want to see your creativity in tackling problems, so don’t hold back on showcasing your innovative approaches!
Tailor Your Application: Read the job description carefully and tailor your application to match our needs. Mention how your background aligns with our focus on predictive modelling and your enthusiasm for R&D processes.
Be Yourself: We’re a small team, so let your personality shine through! Share your interests and what excites you about the role. We love candidates who are passionate and eager to learn from industry experts.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Longshot Systems
✨Know Your Models Inside Out
Make sure you’re well-versed in the machine learning models you’ve worked with. Be ready to discuss their strengths and weaknesses, and how you’ve applied them in past projects. This will show your depth of knowledge and ability to critically evaluate your work.
✨Brush Up on Your Python Skills
Since you'll be implementing models in Python, it’s crucial to be comfortable with the language. Practice coding challenges related to data manipulation and model implementation. Familiarity with libraries like Pandas, NumPy, and Scikit-learn will definitely give you an edge.
✨Prepare for Scenario Questions
During the technical interview, expect scenario-based questions that test your problem-solving skills. Think about how you would approach real-world modelling problems, and be prepared to explain your thought process clearly and logically.
✨Show Your Creativity
Longshot Systems values innovative thinking, so come prepared with examples of how you've tackled problems creatively in the past. Whether it’s a unique modelling approach or a novel solution to a challenge, showcasing your creativity can set you apart from other candidates.