Advanced Data Analysis Engineer

Company Description

Snke OS™ is a universally deployable digital B2B platform, founded in 2020 & headquartered in Munich. Emerging technologies continue to drive a digital transformation in the healthcare economy. Our founders recognized the potential for value creation by decoupling & deploying their best-in-class platform & team so that other companies can scale up & innovate efficiently. Fueled by AI & big data analytics, Snke OS delivers the platform & infrastructure that enables partners across the healthcare industry to deploy digital solutions for safer & more efficient interventions.

The 150-person Snke OS team brings a wealth of experience to the new company with backgrounds in large platforms, digital health & software-driven medical technology. Let’s impact the industry together! 

Job Description

For our growing Snke Anatomy division, we are looking for an Advanced Data Analysis Engineer.

In our department we develop complex software solutions to automatically analyze medical data (in particular images) in order to obtain detailed understanding of a patient’s anatomy. To this end, we employ state-of-the-art, data driven methods and algorithms (making use of deep learning and computer vision approaches) which we develop from early prototypes to ultimately released and validated medical products.

As a Data Analysis Engineer, you will be part of our project team and one of the software experts for data management and performance analysis. In this role, you will accompany the complete development process:

• From the beginning, you will be working closely with the development teams to continuously analyze and monitor the performance of our algorithms.
• You will select representative test data pools, choose suitable metrics, refine acceptance criteria together with project managers and stakeholders, and implement statistical approaches to properly quantify the evolution of the performance.
• You will handle large amounts of medical data and dive deep to identify any strengths and weaknesses of our algorithms.
• You will thereby also obtain a detailed understanding of the properties of medical images and the requirements of our stakeholders.

In order to make your work scalable and reproducible, you will actively contribute to further developing our internal data processing and testing platform, using Python and its data science libraries. Ultimately, you will also be responsible for the validation and contribute to the market release of our solutions in compliance with regulatory requirements, by comprehensively documenting your evaluation results.

In summary, this position combines elements of several technical and organizational jobs, including data engineering, statistical analysis, computer science, project engineering, and biomedical engineering.

Qualifications

• Education in an engineering or natural science discipline
• Demonstrated experience in the analysis and visualization of complex data, including  application of statistical methods for hypothesis testing and parameter estimation
• Profound programming knowledge in Python, including standard data science libraries like NumPy, Pandas, SciPy, Matplotlib, etc.
• Experience in analyzing and presenting the performance properties of complex software systems
• Experience in working with medical data (in particular images) as well as with the corresponding regulatory requirements is a plus
• Eagerness to be part of a high-skilled, dynamic team where you can closely interact with experts in different roles to bring our products successfully to the market
• Fluency in English

Additional Information

• A mutually-supportive, international team
• Opportunity to build career experience in an exciting international company with a lasting impact on medical technology based in Munich
• Flexible working hours
• Secure bicycle storage room
• Subsidized catering service 
• Subsidized Gold Gym membership and access to Brainlab headquarters modern gym
• Centrally located, modern work spaces with a great 212m² roof terrace

Ready to apply? We look forward to receiving your online application including your first available start date.

Contact person: Daniel Sypli