We are looking for a talented data scientist/algorithm engineer who is passionate about biomedical applications and has a strong background in machine learning, pattern recognition, signal processing and time-series analysis. The successful candidate will join the data science team and will be responsible for design and development of new state-of-the-art classification algorithms that will take the field of EEG neurodiagnostics to the next level.
What you'll do:
- Use time-series analysis, statistical signal processing and machine learning techniques to design classification algorithms for various neurological indications
- Analyze data for trends and patterns, and interpret data with a clear objective in mind
- Collaborate with business and clinical stakeholders to define project needs and communicate results of the models/analytical solutions designed
- Select and implement appropriate evaluation metrics to assess the performance of algorithms and models, considering both technical accuracy and clinical relevance.
- Document and validate models and perform statistical analysis to comply with regulatory requirements for medical device algorithms
- Mentor and guide junior data scientists and interns, fostering their growth by providing technical direction, feedback, and support
- Manage multiple projects independently, effectively prioritizing tasks and aligning deliverables with key milestones to ensure timely and successful outcomes
- Stay updated with the latest advancements in machine learning and neurodiagnostics to ensure the algorithms are state-of-the-art
What We're Looking For:
- PhD in Electrical Engineering, Computer Science, Statistics, or equivalent disciplines
- 7+ years of relevant research and/or industry experience in signal processing, filtering, statistical data analysis, time-series analysis, pattern recognition, feature engineering, machine learning and algorithm development
- Proficient in Python and/or Matlab and/or R or similar programming languages
- Experience and interest in biological signal processing and algorithm development for biomedical applications
- Strong analytical skills, detail-oriented and collaborative
- Experience with large-scale datasets, including preprocessing, cleaning, and handling noisy or imbalanced data in a biomedical context
- Proven ability to work independently, define scope and and manage complex technical projects from concept to deployment
- Experience with advanced machine learning techniques, such as deep learning architectures (e.g., CNNs, RNNs) and their application to time-series data
- Strong preference for experience in neurodiagnostics or EEG data processing and algorithm development
