Senior Data Scientist

Master’s or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or related field
3+ years of professional experience in data science or machine learning roles
Demonstrated experience leading data science projects or teams
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)
Strong analytical thinking and problem-solving abilities
Excellent communication and presentation skills
Proven ability to influence cross-functional teams and stakeholders

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
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
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
Partner with data engineering teams to ensure the availability of robust data pipelines
Recommend and implement data tools, frameworks, and platforms to enhance workflows
Communicate complex findings and recommendations to technical and non-technical stakeholders
Translate business objectives into data science tasks and projects