Description

You will lead the design, development, and optimization of predictive models for elderly fall risk assessment.

Responsibilities

• Design and optimize predictive models using machine learning and deep learning techniques.
• Develop ETL pipelines to preprocess and integrate healthcare data from multiple sources.
• Manage team deliverables, coach members, and guide technical problem-solving.
• Collaborate with clinicians and cross-functional teams to align AI solutions with clinical workflows.
• Evaluate model performance and refine algorithms for accuracy and generalizability.
• Ensure compliance with healthcare data regulations including HIPAA and GDPR.

Required Skills

• 8-11 years of experience in data science, including at least 2 years in the healthcare domain.
• Master's or PhD in Data Science, Computer Science, Statistics, Bioinformatics, or a related field.
• Proficiency in Python or R.
• Hands-on experience with TensorFlow, PyTorch, or Scikit-learn.
• Experience leading AI projects in healthcare startups, hospitals, or MedTech companies.
• Strong knowledge of statistics, probability, and feature engineering.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Ability to publish research findings related to healthcare data science.
• Experience working with Electronic Health Records (EHR), wearable, or sensor data.

Preferred Skills

• Knowledge of biomechanics or human movement analysis.
• Experience with explainable AI (XAI) and interpretable ML models.

Key Skills

Education

Any Graduate