The Role
Lead complex data science projects, mentor junior team members, and develop machine learning models for cardiac monitoring solutions.
Summary Generated by Built In
Cardiosense is a rapidly growing, venture-backed medical AI company that is redefining how we detect, monitor, and manage heart disease. We're developing novel wearable sensors and advanced machine learning algorithms that translate raw physiological signals into clinically actionable, digital biomarkers used to detect early signs of cardiac worsening, guide personalized therapy, and improve patient outcomes.
Our team brings together experts in data science, biosignal analysis, and medicine united by a common mission to identify and combat preventable cardiac disease. Cardiosense's solutions are built on over a decade of clinical research and we continue to collaborate with the world's leading academic institutions to introduce the next generation of cardiac monitoring and disease management.
We are seeking a highly experienced Senior Data Scientist to lead complex projects, mentor junior team members, and develop cutting-edge machine learning models and analytics tools. The ideal candidate will have a proven track record of solving high-impact business problems using data-driven methodologies and be passionate about advancing our organization's data capabilities.
KEY RESPONSIBILITIES
- Data Strategy
- Collaborate with cross-functional teams to identify opportunities for leveraging company data to drive business 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.
- Own the end-to-end lifecycle of models, from research and prototyping to production and monitoring.
- 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 complex findings and recommendations to technical and non-technical stakeholders.
- Translate business objectives into data science tasks and projects.
QUALIFICATIONS
- Education
- Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or related field.
- Experience
- 3+ years of professional experience in data science or machine learning roles.
- Demonstrated experience leading data science projects or teams.
- Technical Skills
- Expertise in programming languages such as Python, R, or Scala.
- Strong proficiency in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn).
- Experience with big data tools (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
- Soft Skills
- Strong analytical thinking and problem-solving abilities.
- Excellent communication and presentation skills.
- Proven ability to influence cross-functional teams and stakeholders
PREFERRED QUALIFICATIONS
- Industry experience in healthcare or medical device environment.
- Familiarity with MLOps and automated pipelines.
Cardiosense is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, ethnicity, religion, disability status, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Top Skills
AWS
Azure
GCP
Hadoop
Python
PyTorch
R
Scala
Scikit-Learn
Spark
TensorFlow
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The Company
What We Do
Contact: [email protected]
Cardiosense is building a physiological waveform data platform that leverages novel multi-modal sensors and industry-leading AI to develop predictive biomarkers for pre-symptomatic disease detection and enable personalized therapy.
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