Algorithms Engineer Trainee

Summary

Join Sword Health, a Forbes Best Startup Employer, and be part of a mission to free two billion people from pain. As a Sword Trainee, you'll contribute to impactful projects over 12 months, working with a global team to build AI-powered solutions. You will design and implement algorithms, perform data analysis, and collaborate with various teams. This role requires a Master's degree in a relevant field, strong Python skills, and the ability to solve complex problems. The program offers a stimulating environment, access to a health and well-being program, learning opportunities, and a remote or hybrid work policy.

Requirements

• Master’s degree in Engineering, Computer Science, Physics or Mathematics
• Ability to solve complex problems with software
• Solid knowledge of Python
• Good technical foundation (data science and related fields) but above all ability to learn about new technical topics
• Ability to visualize and interpret data of different types
• Critical thinking, self-direction, results-oriented mindset
• Ability to collaborate effectively with technical and non-technical stakeholders and within the team

Responsibilities

• Design and implement algorithms and tooling to support our developments in several fronts, for example, to track pelvic floor movement tracking, sleep, activity and stress
• Perform data analysis to retrieve insights regarding how to improve existing algorithms and user experience
• Troubleshoot, debug and maintain documentation
• Contribute to the quality of the team’s output by developing and executing test plans and creating internal tools and scripts for automation and testing
• Communicate with product and clinical team to refine requirements and scope of work

Benefits

• A stimulating, fast-paced environment with lots of room for creativity
• A start of a bright future at a promising high-tech startup company
• Access to our health and well-being program (digital therapist sessions)
• Learning opportunities with tailored mentoring
• Remote or Hybrid work policy