ANALYST, IT, SR

Position Summary

The Data Science Engineer is responsible for designing, developing, and maintaining data-driven software solutions supporting the Spae Lab (PI: James Jung MD PhD) in Dept. of Surgery, Duke Institute for Health Innovation (DIHI) and other data solutions supporting the Department of Surgery within the Laboratory Transformative Administration (LTA). This position will act as a liaison between the data science, data engineering, and solution architect team members to ensure that machine learning models are developed and evaluated through robust processes and effectively integrated into clinical care. This position will interface directly with clinical end users to identify user requirements, design and prototype the user experience, and support the development and implementation of clinical workflow applications. This position will work closely with the Dr. Jung, DIHI and LTA teams to identify and pursue opportunities to either operationalize or commercialize technologies with relevant external partners. Lastly, the Data Science Engineer will help teach students and trainees involved in workforce development programs. The Data Science Engineer is expected to have expertise in statistics and machine learning, software development, and human centered design to effectively develop machine learning solutions to improve care at Duke Health. The data science engineer will maintain comprehensive and contemporary knowledge of machine learning and software development best practices, with a focus on product development and commercialization. The position reports directly to Dr. Jung and DIHI Program Director, with a dotted line to Director of Data Analytics and Innovation in the Department of Surgery.

Duties and Responsibilities of Position:

• Development, validation, and implementation of machine learning systems – 50%
  • Works directly with Dr. Jung, data science lead, quantitative science trainees, and clinical trainees who are involved in model development and validation within DIHI and the Department of Surgery, depending on origination of the project.
  • Develops utilities and frameworks to standardize and enhance the development and validation of machine learning systems
  • Develops and updates monitoring systems to ensure that any implemented machine learning model continues to perform as specified
  • Reviews code and performs evaluations of previously built machine learning models before integration into technical infrastructure
  • Maintains contemporary knowledge of advances in machine learning to ensure that emerging technologies are incorporated into Spae lab, DIHI and LTA development efforts
• Design and development of clinical workflow applications to put machine learning systems into clinical practice – 20%
  • Works directly with clinical and operational stakeholders to identify requirements, design user experience, and prototype solutions
  • Works directly with solution architects to support the development of workflow applications
  • Develops utilities to enable rapid testing, evaluation, and iteration of workflow applications
• Development and maintenance of technology infrastructure to support portfolio of machine learning systems – 15%
  • Works directly with data engineering and solution architect team members to optimize technology infrastructure for rapid implementation of machine learning systems
  • Identifies opportunities to enhance data structures to enable more effective maintenance and updating of machine learning systems
  • Develops utilities to enable comparison of multiple model versions integrated into infrastructure and rapid updating and evaluation of new model versions
• Diffusion and dissemination of machine learning products – 15%
  • Works directly with Dr. Jung, DIHI Program Director and/or the Director of Data Analytics and Innovation to identify opportunities to externally validate, diffuse, and commercialize technology solutions
  • Participates in dissemination efforts via academic writing, conference presentations, and internal and external communications related to DIHI and Department of Surgery projects

The position assists and leads in performing the following functions:

1. Develops, evaluates, and implements data science solutions and machine learning models
2. Develops and maintains technology infrastructure optimized for model deployment, monitoring, and updating
3. Develops frameworks and utilities to enhance ability of trainees and external users to be able to rapidly test and evaluate novel machine learning models

Education:

Bachelor’s degree in a statistics, mathematics, engineering, computer science or related quantitative field is required. Master’s degree preferred or equivalent work experience.

Experience:

Preferred Experience: Position requires four years related experience. A Masters degree can substitute for two years of experience.

Knowledge, Skills, and Abilities:

• Strong background in software development with experience in back-end and front-end development
• Strong background in Python programming
• Strong background in statistics with experience developing, evaluating, and implementing machine learning models
• Strong background in data management including Oracle or SQL.
• Prior experience with clinical, EHR and/or administrative health data required.
• Strong knowledge of machine learning methods, software development, and presentation techniques.
• Experience working closely with data scientists, data engineers, solution architects, and business analysts bringing software products to market.
• Excellent analytical and problem-solving ability.
• Healthcare/Research industry experience required.
• Documenting and analyzing workflow and clinical processes
• Creating data solutions to support business processes
• 4+ years of experience in requirements gathering and data analysis

Preferred Qualifications

• Data science / machine learning with healthcare data
• Experience bringing software products to market
• Development of extract, transform, and load (ETL) pipelines to support data-driven software applications
• Experience identifying strategic opportunities for novel product development
• Knowledge of software development, machine learning, and technology infrastructure

Minimum Qualifications

Education

Refer to Job Description

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