Job description
About the job Data Science Intern
About Prorizon
Prorizon is a digital health tech start-up using an integrated mind-body approach to enable optimal health and performance for todays youth in high pressure environments. Prorizon is building the new technology needed to optimise mind and body, reducing the mental health crisis in high pressure environments, enabling young people to thrive. Prorizons starting point and alpha users are young athletes whose mental health is often overseen Leading to an imbalance (Prorizon strives to bringing that balance back).
About the role
Prorizon is looking for someone who has the ability to work with large data sets and to develop and test relevant algorithms and models, someone who is passionate about working with data to develop complex solutions, this is integral to the success of their product. The data science intern will work closely with Prorizons Science & R&D Director and Data Science Advisor.
What you'll do
- Oversee and support the development of junior data-science and research interns.
- Develop and run machine learning models using, e.g., Python.
- Design and deliver visual data and insights that are clear and relevant to athletes.
- Communicate and collaborate with our data science advisor to ensure data reliability.
- An ability to work independently and as part of a team.
- Work with real-time data to inform the development of our product.
- Deliver progress updates to the wider team.
- Generate ideas to improve engagement of sporting audiences with their health data.
Must-have Requirements
- A PhD degree program in math, computer science, data science or other quantitative fields.
- Knowledge of and experience in machine learning and data science theory, techniques, and tools.
- Skilled in using Python and/or R in day-to-day work.
- Ability to work with real-world data through exploratory data analysis and data visualisation.
- An independent, creative problem-solver with a can-do attitude.
- Flexibility to work in a fast-paced and fast-changing environment.
- Common sense to see when something is not working and the capability to inform next steps
- Driven by using your skills and data for good.
Desirable
- Passion for sports.
- Previous experience and evidence of machine learning projects.
- Available for up to 6 months (shorter terms will be considered).
Location: Hybrid (remote + London)
Compensation: £12 per hour, plus expenses
Working hours: 16 hours per week
Start Date: ASAP
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