Research Data Analyst

POSITION OBJECTIVE

Working under general supervision, the Advanced Data Analytics Research Analyst serves as a specialized role in the Cardiovascular Research Institute managing multiomic platforms using enabling Artificial Intelligence (AI) and machine learning approaches as part of a precision medicine research program. The analyst will manage the development and application of advanced machine learning approaches to delineate the health impact of interventions in both experimental and human trials.

The institute is engaged in the integration of large-scale biological datasets to address gaps in knowledge between genomic and environmentally mediated risk. The lab is on the cutting edge of discovery and has interests in the interface of genomic and environmental factors that modulate risk for future heart disease. The laboratory leverages several unique data sets including cutting edge imaging science juxtaposed with environmental variables that monitor the environment to develop next general approaches for personalized medicine.

The resources that the lab leverages include the Center for Advanced Heart and Vascular care (CAHVC) is a futuristic academic-corporate partnership with Siemens and Medtronic to develop the next generation of innovative technologies that combine imaging with intervention guided by robotics and artificial intelligence.

• Manage the development and application of advanced machine learning approaches to delineate the health impact of interventions in both experimental and human trials.
• Create and manage predictive models using health information and imaging datasets to predict risk and response to therapy.
• Collect, clean, and preprocess data from various sources to ensure its quality and relevance for analysis (25%).
• Manage intelligent integration of patient profiles to delineate susceptibility to coronary heart disease.
• Collect, preprocess, and analyze data to train and evaluate machine learning models.
• Utilize data visualization techniques to effectively communicate complex findings and recommendations to stakeholders.
• Participate in the development and deployment of data analytics platforms and tools (25%).
• Utilize novel multiomic platforms to predict risk in animal models.
• Collaborate with data scientists, software engineers, and IT teams to ensure seamless integration of machine learning solutions into existing infrastructure.
• Run predictive and prescriptive analytics models to leverage past historical data to see trends, patterns, and anomalies, predict future ramifications if those trends continue, and identify the best next steps (25%).
• Apply advanced statistical and machine learning techniques to analyze large datasets and extract actionable insights related to disease pathways in animal models relevant to humans.
• Collaborate with cross‑functional teams including engineers, architects, and project managers to identify data‑driven solutions and optimize processes.
• Develop and implement predictive models, algorithms, and data‑driven decision‑making tools (20%).

• Stay updated with the latest advancements in data science, machine learning, and artificial intelligence to identify opportunities for innovation and improvement within the organization (5%).
• Perform other duties as assigned (1%).

• Departmental:
  Regular contact with research collaborators and principal investigators to provide information and to receive instruction.
• University:
  Occasional contact with other departments within the university to provide information and gather instruction.
• External:
  Limited external contacts.
• Students:
  Occasional contact with students to provide information and instruction.

This position has no direct supervision of staff employees.

Education/

Experience:

Bachelor of Science required with knowledge and experience with R and other related data visualization software in a health environment and 0 to 1 year of experience. Strong background in one or more areas of machine learning (Bayesian networks, neural networks, Markov Models, convolutional networks, etc.) Exposure to computational and/or systems biology…