Job Description

 

Harris Health System is the public healthcare safety-net provider established in 1966 to serve the residents of Harris County, Texas. As an essential healthcare system, Harris Health champions better health for the entire community, with a focus on low-income uninsured and underinsured patients, through acute and primary care, wellness, disease management and population health services. Ben Taub Hospital (Level 1 Trauma Center) and Lyndon B. Johnson Hospital (Level 3 Trauma Center) anchor Harris Health’s robust network of 39 clinics, health centers, specialty locations and virtual (telemedicine) technology. Harris Health is among an elite list of health systems in the U.S. achieving Magnet® nursing excellence designation for its hospitals, the prestigious National Committee for Quality Assurance designation for its patient-centered clinics and health centers and its strong partnership with nationally recognized physician faculty, residents and researchers from Baylor College of Medicine; McGovern Medical School at The University of Texas Health Science Center at Houston (UTHealth); The University of Texas MD Anderson Cancer Center; and the Tilman J. Fertitta Family College of Medicine at the University of Houston.

Skills / Requirements

Job Summary 

Harris Health seeks an experienced Data Scientist to join its Data and Analytics department, which supports system initiatives to transform the organization's model of care, encompassing the continuum of care coordination, inpatient, outpatient, ambulatory, acute and chronic care, social determinants of health, value-based financing strategies, community collaboration and outreach. This experienced data scientist is responsible for curating the data assets for their operational unit in alignment with Harris Health's analytics strategy, including embedding analytic capabilities for stratifying patient populations by risk, targeting interventions, supporting redesign of patient workflow, and measuring and monitoring results.  Additionally, this is a uniquely qualified individual with domain knowledge in healthcare program design and evaluation plus the technical fluency to bridge the gap between data and operational teams. The Principal Data Scientist is experienced in coaching and deliverable review, in working in a matrixed organization to advance cross-departmental initiatives, and foster strong partnerships. Working at the fourth largest safety-net healthcare system in the nation, the successful candidate will also be able to demonstrate a commitment to the people and communities we serve.  The Principal Data Scientist provides ultimate technical expertise in the analysis, design, development, and implementation of analytics solution strategies and frameworks.  The Principal Data Scientist is responsible for deconstructing and understanding vendor capabilities in relation to analytics infrastructure and functionality, determining optimal use of those component parts, and communicating best practices to the analytics development community throughout Harris Health.  

Minimum Qualifications 

Degrees:
Master's Degree in Data Science, Informatics, Statistics Actuarial Sciences, Computer Science, Mathematics or related field 

Or 

PhD Data Science, Informatics, Statistics Actuarial Sciences, Computer Science, Mathematics or related field (Preferred)

Work Experience:
Seven (7) Years Work Experience Experienced data science computer programmer SQL and SAS or python or R or SPSS with experience in the areas of reporting and analytics development, database design, and/or data layer or database application programming. Including six (6) years experience providing strategic direction for healthcare data platforms in coordination with organizational and departmental leadership; Experience vetting and implementing analytic solutions that are responsive to stakeholder needs and training staff in technical skills. 

Management Experience:
Five (5) years of Project Management Experience managing complex initiatives requiring a range of project skills, including ability to formulate strategies, advance organizational priorities, and delegate effectively to multiple team members; Supervisory experience, including demonstrated ability to coach, mentor, and share knowledge with staff, as appropriate.
Strong background in Epic EMR Clarity and Caboodle databases. The ideal candidate will be an expert in SQL and have a proven track record of leveraging healthcare data to drive strategic decisions and improve clinical and operational outcomes. This role involves collaborating with cross-functional teams to design, implement, and analyze complex data models and algorithms
 

Highly preferred candidate will have the the following:

  1. Educational Background:
    Ph.D. or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
  2. Technical Skills:
    Proficiency in programming languages such as Python, R, and SQL.
    Experience with machine learning frameworks (e.g., TensorFlow, PyTorch).
    Strong understanding of statistical analysis, data mining, and predictive modeling.
    Familiarity with big data technologies like Hadoop, Spark, and cloud platforms (e.g., AWS, Azure).
  3. Experience:
    Extensive experience in data science roles, with a proven track record of leading complex projects.
    Experience in managing and mentoring a team of data scientists.
    Demonstrated ability to translate business problems into data-driven solutions.
  4. Leadership and Communication:
    Strong leadership skills with the ability to inspire and guide a team.
    Excellent communication skills to effectively convey complex technical concepts to non-technical stakeholders.
    Ability to influence decision-making at the executive level.
  5. Certifications:
    Relevant certifications such as the Principal Data Scientist (PDS') certification can be a plus.
  6. Strategic Vision:
    Ability to drive innovation and strategic initiatives within the organization.
    Experience in shaping data science trends and driving organizational growth through data-driven strategies

    Communication Skills:
    Above Average Verbal Communication (Heavy Public Contact)
    Writing/Reports

    Job Attributes 

    Knowledge/Skills/Abilities:
    Analytical, Design, Statistical, Other; Implementation methodology knowledge and skills, Computer Programming; SQL and SAS or python, R, SPSS

    Other Requirements:
    Expertise regarding key trends in health metrics for healthcare delivery and managed care systems; Excellent analytic and communication skills, including the ability to tailor communication for various audiences and to facilitate understanding of complex or technical concepts; Diligence, attention to detail, and an unwavering commitment to high-quality work.

Typical duties that may be performed

1. Stays current with emerging technologies relevant to the creation, storage, retrieval, analysis, and dissemination of data and analytic products.

2. Establishes and maintains data standards, best practices, processes, procedures and establishes and maintains capability roadmaps.

3. Educates customers/partners of all sizes on the value proposition of data and participates in deep architectural discussions to ensure solutions are designed for successful deployment.

4. Captures and shares best-practice knowledge amongst the analytics developer community.

5. Builds deep relationships with senior technical individuals within customers/partners to enable them to be data advocates.

6. Acts as a technical liaison between customers/partners, service engineering teams and support.

7. Defines and develops reusable data architecture deliverables, artifacts and building blocks (e.g. conceptual models, logical models, physical models, etc.). Must be well versed in business processes and capable of understanding organizational workflows and complexities.

8. Provides thought leadership, develops strategies and methods for analyzing and profiling data, and assists data analysts in the application of methods to ensure effectiveness and efficiency.

9. Advises analytics development teams on best practices and shapes the future landscape of data usage and analytics development.

10. Applies high level analytical techniques on data sets to find patterns and anomalies.

11. Uses data analysis results at all levels to provide recommendations and designs solutions to improve data manag

Application Instructions

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