At a Glance
- 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, bonus scheme, private healthcare, and gym membership.
- Other info: Flexible working hours and a supportive team culture await you.
- 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.
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 in London employer: Longshot Systems
Longshot Systems is an exceptional employer for those passionate about machine learning and sports analytics, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from opportunities for professional growth through hands-on experience with cutting-edge technologies like Docker, Kubernetes, and cloud platforms, all while contributing to impactful projects in the fast-paced world of sports betting. Located in a vibrant tech hub, the company provides a stimulating environment where creativity and technical expertise thrive.
StudySmarter Expert Advice🤫
We think this is how you could land Graduate Machine Learning Researcher in London
✨Tip Number 1
Get your networking game on! Reach out to current employees at Longshot Systems on LinkedIn. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Prepare for those interviews like a pro! Brush up on your machine learning concepts and be ready to discuss your past projects. We want to see your passion and creativity shine through!
✨Tip Number 3
Show us your problem-solving skills! During the assessment day, think outside the box when tackling the modelling problem. We love innovative approaches that demonstrate your unique thinking.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Longshot Systems.
We think you need these skills to ace Graduate Machine Learning Researcher in London
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 how you can contribute to our team, so don’t hold back on showcasing your skills!
Tailor Your Application:Take a moment to customise your application for the Graduate Machine Learning Researcher role. Mention specific projects or experiences that relate to predictive modelling and how they align with what we do at Longshot Systems.
Be Creative:We love innovative thinkers! In your application, feel free to share any unique approaches you've taken in past projects or ideas you have for improving existing methodologies. Show us your creative side!
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. Plus, it makes the whole process smoother for everyone involved.
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 to real-world problems. 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 a modelling challenge using historical data. Practising these types of questions can help you articulate your thought process clearly.
✨Show Your Creativity
Longshot Systems values innovative thinking, so don’t hesitate to share unique ideas or methodologies you’ve considered in your past projects. Discussing how you’ve approached problems creatively will demonstrate your fit for a role that requires autonomy and innovation.
