Cardiosense is a digital health company that operates at the intersection of wearable technology and artificial intelligence to improve patient health. Our mission is to use physiological waveform data to predict cardiac illness and enable early interventions so people can enjoy healthier, longer lives.
To achieve our mission we are building a physiological waveform AI platform to develop predictive biomarkers to detect and manage cardiac disease. The company has developed a suite of novel digital tools, multi-sensor devices, and analysis algorithms for use by care providers to detect clinical worsening earlier, inform personalized therapy, and improve patient outcomes.Our team brings together experts in data science, electronics, and healthcare and has partnered with leading healthcare and academic institutions to introduce the next generation of patient waveform monitoring and analytics solutions.
are seeking a highly motivated Data Scientist Intern to develop cutting-edge machine learning models and analytics tools. The ideal candidate will have training in using machine learning and biosignal processing to solve complex healthcare problems. ABOUT THE ROLEWe are seeking a highly motivated Data Scientist Intern to develop cutting-edge machine learning models and analytics tools. The ideal candidate will have training in using machine learning and biosignal processing to solve complex healthcare problems.
KEY RESPONSIBILITIES
- Data Strategy
- Collaborate with cross-functional teams to identify opportunities for leveraging company data to develop machine learning solutions.
- Collaborate with clinical teams and external vendors to facilitate data collection.
- Model Development & Deployment
- Design, develop, and deploy scalable machine learning models and advanced analytics.
- Apply digital signal processing techniques to physiological waveforms (PPG, ECG, SCG, etc.) and build novel machine learning algorithms for hemodynamic assessment.
- Optimize existing algorithms and pipelines to improve efficiency and performance.
- Advanced Analytics
- Perform exploratory data analysis to extract actionable insights.
- Develop predictive, prescriptive, and descriptive analytics to inform decision-making.
- Work with structured and unstructured data to uncover trends and patterns.
- Data Infrastructure & Tools
- Partner with data engineering teams to ensure the availability of robust data pipelines.
- Recommend and implement data tools, frameworks, and platforms to enhance workflows.
- Stakeholder Engagement
- Communicate findings and recommendations to technical and non-technical stakeholders.
QUALIFICATIONS
- Education
- Bachelors in Electrical Engineering, Computer Science, Statistics, Mathematics, or related fields. Master’s or PhD student/graduate preferred.
- Experience
- 2+ years of experience in the field of data science or machine learning with a focus on biomedical applications.
- Technical Skills
- Expertise in programming languages such as Python, R, or Scala.
- Exposure to machine learning frameworks (TensorFlow, PyTorch, Scikit-learn).
- Soft Skills
- Strong analytical thinking and problem-solving abilities.
- Excellent communication and presentation skills.
- Proven ability to influence cross-functional teams and stakeholders.
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