At a Glance
- Tasks: Design and implement innovative ML models using Python for predictive tasks.
- Company: Join a small, focused company with a strong emphasis on R&D.
- Benefits: Enjoy hybrid working, autonomy, and mentorship from industry experts.
- Other info: Collaborative environment with opportunities for professional growth.
- Why this job: Make an impact in the exciting field of machine learning and quantitative modelling.
- Qualifications: Recent graduates with a passion for machine learning and programming skills.
The predicted salary is between 63000 - 77000 £ per year.
Longshot Systems is recruiting a Graduate Machine Learning Researcher to join our quantitative modelling team in London.
You will design, test, and implement new ML models in Python, tackling predictive tasks based on historical event data.
The role offers high autonomy, involvement in all stages of R&D from concept to production, and the opportunity to learn from experienced industry experts in a small, focused company.
Hybrid working with office Thursdays in London.
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ML Researcher — Quantitative Modelling (Hybrid) employer: TargetJobs UK
At targetjobs UK, we pride ourselves on being an excellent employer, offering a supportive work culture that fosters innovation and collaboration. Our Graduate Fire Engineer role not only provides competitive benefits such as 25 days holiday and flexible working options but also presents unique opportunities for professional growth in the thriving Cherwell District. Join us to make a meaningful impact in fire safety while enjoying a balanced work-life environment.
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We think this is how you could land ML Researcher — Quantitative Modelling (Hybrid)
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We think you need these skills to ace ML Researcher — Quantitative Modelling (Hybrid)
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!
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✨Brush Up on Your Statistics
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