Become part of a very successful Medtech startup that has operated for over 5 years and is on its way to skyrocket in the field of analyzing human psychology and developing an AI engine that helps psychologists to make better diagnoses.
Starting in gaming, optimized for human potential and health: Take that opportunity to shape a ground-breaking idea from the early days!
What my client company has to offer :
- Top-of-market compensation
- Flexible work-schedule
- State-of-the-art equipment and work station
- Learning budget & access to curated means of personal development
- Support with relocation & visa application
- Flexible work-from-home policy
WHAT YOU WILL DO
- Research, design, implement and refine state-of-the art algorithms to optimally collect and analyze psychometric data
- Perform complex statistical analyses on our large proprietary data sets
- Work closely with ML engineers, psychometricians, software engineers, researchers and UX team to incorporate the latest findings from psychometrics, machine learning and psychological research into a working product
YOUR BACKGROUND
- 4+ years of relevant practical experience in applied statistics, machine learning, data science or a related field
- PhD in mathematics, statistics, computational neuroscience, psychometrics, econometrics, or related quantitative field
- Exceptional grasp of probability and statistics fundamentals
- Strong command of Python
- Hands-on experience with Bayesian modeling and computation (MCMC, variational inference, etc.)
- Hands-on experience with leading commercial cloud computing platforms
- Proven ability to document and communicate scientific work clearly, concisely and precisely
HOW YOU STAND OUT
- Hands-on experience working with psychometric data and data from surveys or psychological instruments
- Hands-on experience with machine learning, especially unsupervised and semi-supervised learning
- Hands-on experience of python probabilistic computing and deep learning frameworks and libraries (especially PyTorch)
- Working familiarity with modern infrastructure and tools (e.g. Kubernetes, Docker, AWS) and large-scale data processing technologies (e.g. SQL, BigQuery, Hadoop, Spark)
- Experience in working in a small data science/engineering team in a fast-paced, startup environment
To learn more about this opportunity, please reach out to Eva Sassnick with your CV.
