Digital Health Data Scientist (Finance)

About Rice:

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Position Summary:

The Digital Health Data Scientist for the Houston Methodist-Rice Digital Health Institute (DHI) will play a key role in the research and development of advanced digital health solutions. Working closely with interdisciplinary teams of clinicians, engineers, and researchers, the Digital Health Data Scientist will apply data science techniques to healthcare datasets to drive innovations in bio-signal processing, risk prediction, precision medicine, computational biology, and more. The ideal candidate will have deep experience in healthcare data, including EMR, bio-signals, imaging, or computational biology, and be adept at translating complex data into actionable insights to improve patient outcomes.

The Digital Health Data Scientist will contribute to the development of scalable solutions and help build the foundation for predictive analytics, machine learning models, and data-driven healthcare innovations. This position will collaborate with both the Houston Methodist and Rice University teams, facilitating the translation of data science research into practical clinical applications.

Ideal Candidate Statement:

We are seeking an accomplished and visionary leader to serve as the Digital Health Data Scientist of the Digital Health Institute (DHI), a joint venture between Houston Methodist and Rice University. The institute comes with a significant commitment from both Houston Methodist and Rice University. The Digital Health Data Scientist will be responsible for overseeing the operational rollout, strategic development, and expansion of the Institute, leveraging state-of-the-art research in digital health to drive innovation in patient care. This is a unique opportunity to shape the future of healthcare by merging cutting-edge technology with clinical expertise to deliver impactful solutions across the health ecosystem.

On campus position: "This position is exclusively on-site, necessitating all duties to be performed in-person. Per Rice policy 440 , work arrangements may be subject to change."

Salary is commensurate with experience and qualifications. *Exempt (salaried) positions under FLSA are not eligible for overtime.

This position is funded by a grant, soft and/or restricted funds. Continued employment is contingent on the renewal of funding.

Minimum Requirements:

• Ph.D. Degree with a strong focus on Data Science, Computer Science, Statistics, Bioinformatics, Electrical Engineering or a related field with a strong focus on healthcare applications.
• Minimum of 3 years of experience in data science with a focus on healthcare or biomedical applications. Experience with EMR data, bio-signals, imaging data, or computational biology (at least one modality) is highly preferred.
• Skills:
• Technical Skills:
  • Proficiency in programming languages such as Python, R, SQL, and familiarity with data analysis tools like TensorFlow, PyTorch, or similar machine learning frameworks.
  • Strong background in machine learning, predictive analytics, statistical modeling, and AI techniques.
  • Experience with data preprocessing, feature engineering, and data integration from multiple sources (EMR, imaging, bio-signal, etc.).
  • Knowledge of healthcare data regulations (HIPAA), security, and privacy practices
• Analytical Skills:
  • Ability to interpret and analyze complex healthcare datasets and translate findings into actionable clinical insights.
• Collaborative Skills:
  • Experience working in interdisciplinary teams, including collaboration with clinicians, engineers, and other stakeholders.
• Communication Skills:
  • Ability to present complex data science concepts and research findings clearly to both technical and non-technical audiences.

Preferences:

• Experience with healthcare-specific data analysis tools
• Familiarity with cloud computing platforms (AWS, Azure, Google Cloud) and experience with managing data pipelines and workflows.
• Experience in grant writing and securing research funding for data science projects in healthcare.

Essential Functions:

Data Analysis and Model Development:

• Apply advanced data science techniques such as machine learning, natural language processing (NLP), and statistical modeling to analyze large-scale healthcare datasets.
• Develop and refine predictive models and algorithms to identify patient risks, forecast outcomes, and optimize treatment plans in clinical settings.
• Conduct exploratory data analysis on bio-signals, EMR data, imaging datasets, and other healthcare data to uncover novel insights.
• Collaborate with clinicians to ensure data models are clinically relevant and align with real-world healthcare challenges.

Healthcare Data Integration and Management:

• Lead efforts to integrate various types of healthcare data, including EMR, genomics, wearable sensors, and imaging, into a comprehensive digital health platform.
• Manage and preprocess large-scale datasets to ensure data quality, accuracy, and completeness.
• Work with interdisciplinary teams to curate, clean, and harmonize datasets for use in digital health projects, ensuring compliance with data security and privacy regulations.
• Utilize advanced computational methods to fuse clinical, biological, and geospatial data for developing precision medicine tools.

Collaboration and Clinical Translation:

• Work closely with clinicians, engineers, and other stakeholders to ensure that data-driven solutions are effectively translated into clinical applications.
• Contribute to interdisciplinary research teams by providing data science expertise and support on digital health projects, including risk prediction models, real-time health monitoring systems, and bio-signal analysis.
• Lead collaborations with external partners, including industry, academic institutions, and healthcare providers, to further enhance the development and implementation of data-driven healthcare solutions.

Research and Development:

• Design and implement pilot studies to validate data-driven healthcare models and solutions in real-world clinical settings.
• Contribute to the publication of high-impact research papers, white papers, and presentations in leading journals and conferences in the fields of digital health, AI, and healthcare innovation.
• Stay up to date with the latest research and developments in data science, machine learning, and digital health, continuously improving models and techniques used within the Institute.
• Identify new avenues for research and collaboration that align with the DHI's strategic priorities.

Education and Mentorship:

• Provide mentorship and guidance to junior data scientists, research fellows, and students involved in digital health projects.
• Assist in the development and delivery of training programs and workshops to educate healthcare professionals and engineers on the practical applications of data science in healthcare.
• Participate in educational initiatives and fellowship programs within the DHI, fostering a culture of learning and innovation.

Rice University HR | Benefits: https://knowledgecafe.rice.edu/benefits

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Rice University is committed to ensuring Equal Employment Opportunity and welcoming the fullness of diversity into our candidate pools. Rice considers qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national or ethnic origin, genetic information, disability, or protected veteran status. Rice also provides reasonable accommodations to qualified persons with disabilities. If an applicant requires a reasonable accommodation for any part of the application or hiring process, please contact Rice University's Disability Resource Center at 713-348-5841 or adarice@rice.edu for support.

If you have any additional questions, please email us at jobs@rice.edu . Thank you for your interest in employment with Rice University.