Machine Learning Researcher

Job title:

Machine Learning Researcher

Company

Longshot Systems Ltd

Job description

At Longshot Systems we’re building advanced platforms for sports betting analytics and trading.We’re hiring for Machine Learning Researcher roles within our horse racing team, although prior knowledge of horse racing isn’t required. The primary goal of this team is to improve the predictive power of our models based on fundamental data about horse races. The quality of our models is incredibly important to us and this team has a high impact on the overall success of the company.You will work closely with the CEO, CTO, and Team Lead to design, test, and implement new machine learning models in Python, continually improving our existing state-of-the-art solutions. Due to us being a small startup 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.The ideal candidate will be highly creative and enjoy generating new, innovate 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 and ideally you’ll have experience in doing research on cutting-edge models either in industry or academia.We are a remote-first company, and for this role, we are open to both hybrid candidates—working one day a week in our Farringdon, London office—and fully remote candidates, though we prefer hybrid when possible. 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.We’re open to applicants across a range of experience levels applying to this role with a preference for more experienced / senior hires. Our interview process is as follows: * A 49 minute TestGorilla assessment, with an introductory video about the role from our CEO

  • A 60 minute technical interview with our CEO and/or Team Lead, discussing your previous experience and also discussing some modelling scenarios and how you’d approach them
  • A one day 10am-6pm assessment day, where you’ll be tackling a real modelling problem using data very similar to what we use in practise

RequirementsEssential Skills

  • Very strong mathematical intuition and creativity.
  • Experience across a broad range of Machine Learning and Statistics. The intuition and experience to select the right approach to novel problems and understand the trade-offs involved in that approach as well as understanding the mathematical background to the solution chosen.
  • A practical, pragmatic approach to research and development; experience in taking ideas from concept stage through to production environments.
  • Experience using a range of ML software frameworks in Python
  • Passionate about learning new skills and techniques. Comfortable finding and reading academic papers to generate new research ideas.

Desired Skills

  • Relevant qualifications in Computer Science, Maths, Statistics, Machine Learning etc
  • Software development experience
  • Python / Numpy / Cython execution speed optimisation techniques
  • Unix scripting
  • Git or other version control experience

We encourage you to apply even if you think you may not currently fit all of these requirements – so long as you are willing to work hard and learn, we want to hear from you.BenefitsOur salary range for the role is $120,000 to $200,000, depending on experience and interview performance.List of benefits for UK staff (may differ for international/remote applicants):

  • Participation in the company bonus scheme, typically 10-30% of salary depending on experience.
  • 10% matched pension contributions
  • Private healthcare insurance
  • Long term illness insurance
  • Gym membership

Expected salary

Location

London

Job date

Thu, 10 Oct 2024 22:30:32 GMT

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