Data Scientist Manager

About the role

The Data Science and Biostatistics Unit (DSBU) within the Department of Biomedical and Health Informatics (DBHi) collaborates with researchers across CHOP’s Research Institute to provide data management, analysis, and consultation on methods development, study design, and data analysis. This interdisciplinary team consists of biostatisticians, epidemiologists, data scientists, data analysts, and other methodologists. Staff have expertise in managing and using diverse multimodal healthcare data from a variety of sources and registries associated with electronic health records, clinical trials, administrative and claims datasets, and survey data. DSBU staff have experience across a wide range of machine learning and statistical methodologies, including supervised and unsupervised learning, NLP, computer vision, propensity score matching, multivariate modeling, latent variable mixture models, and geographic information systems.

Responsibilities

• Builds and manages a team of staff scientists in the development and execution of a high-impact data science research program.
• Recruits, hires, and manages staff, including performance management, career development.
• Collaborates with clinical and biomedical researchers to identify data science research questions in clinical and translational research.
• Led data science research experiment planning and execution; where appropriate serves as project Principal or Co-investigator.
• Identifies relevant clinical and translational data science funding opportunities; leads collaborative proposal planning and writing.
• Disseminates research findings through peer reviewed journal articles and professional conference presentations.
• Communicates research methods, implementation, and results to varied audience of clinicians, scientists, analysts, and programmers.
• Guides and mentors junior staff and biomedical researcher collaborators in execution of research projects.
• Serves as the subject matter expert in the implementation of computational algorithms and experiments for test and evaluation as well as advanced data interpretation to assess algorithm performance.
• Sets standards and holds staff accountable for the formulation of analysis plans that meet stringent criteria for reproducibility and measures of significance.
• Serves as the subject matter expert and lead architect in the development of high-quality code implementing models and algorithms as application programming interfaces or other service-oriented software implementations.
• Plays a lead role in educating a varied audience of clinicians, scientists, analysts, and programmers on data science research methods, implementation, and results.
• Mentors junior staff, student workers, co-ops, and research trainees (fellows, post-docs).
• Manages large, complex projects and takes responsibility for major components of larger research initiatives; assigns work to junior staff, identifying, tracking, and reporting on tasks and deliverables against project timelines.

Requirements

• Master's Degree - Required
• Doctorate Analytics, Data Science, Statistics, Mathematics, Computer Science, or related field - Preferred
• At least seven (7) years of applied algorithm development, data science, applied statistics, machine learning, or mathematical modeling projects experience Required
• At least three (3) years of leadership, management or supervisory experience Required
• At least five (5) years of leadership, management or supervisory experience Preferred
• At least ten (10) years of applied algorithm development, data science, applied statistics, machine learning, or mathematical modeling projects experience Preferred

Qualifications

• Expertise and demonstrated ability at acquiring new technical/analytic skills and domain knowledge to support successful contribution to research and development projects is required.
• Expertise formulating analysis plans and selecting appropriate methods is required.
• Expertise using existing machine learning and analytic tools such as ScikitLearn, Weka, R, and Mathematica in either applied academic or professional projects is required.
• Expertise writing code in applied academic or professional projects using one or more of the following languages: Python, Scala, Java is required.
• Familiarity with relational databases (e.g. Postgres, MySQL) strongly preferred.
• Familiarity RESTful web services application programming interfaces preferred.
• Strong verbal and written communications skills with the demonstrated ability to explain complex technical concepts to a lay audience.
• Applied statistics or mathematical modeling experience required.
• Natural language processing experience particularly in the biological and medical domains preferred.
• Experience using distributed computing technologies (e.g. Akka, MapReduce, Cuda) preferred.
• Familiarity with graph, key value, and document data stores (e.g. Neo4j, Hadoop, MongoDB) preferred.
• Experience creating informative visualizations for complex, high dimensional data preferred.
• Experience with probabilistic graphical models, time series predictive models, Markov models preferred.

Skills and Abilities

• Expertise and demonstrated ability at acquiring new technical/analytic skills and domain knowledge to support successful contribution to research and development projects is required.
• Expertise formulating analysis plans and selecting appropriate methods is required.
• Expertise using existing machine learning and analytic tools such as ScikitLearn, Weka, R, and Mathematica in either applied academic or professional projects is required.
• Expertise writing code in applied academic or professional projects using one or more of the following languages: Python, Scala, Java is required.
• Familiarity with relational databases (e.g. Postgres, MySQL) strongly preferred.
• Familiarity RESTful web services application programming interfaces preferred.
• Strong verbal and written communications skills with the demonstrated ability to explain complex technical concepts to a lay audience.
• Applied statistics or mathematical modeling experience required.
• Natural language processing experience particularly in the biological and medical domains preferred.
• Experience using distributed computing technologies (e.g. Akka, MapReduce, Cuda) preferred.
• Familiarity with graph, key value, and document data stores (e.g. Neo4j, Hadoop, MongoDB) preferred.
• Experience creating informative visualizations for complex, high dimensional data preferred.
• Experience with probabilistic graphical models, time series predictive models, Markov models preferred.

Benefits

To carry out its mission, CHOP is committed to supporting the health of our patients, families, workforce, and global community. As a condition of employment, CHOP employees who work in patient care buildings or who have patient facing responsibilities must receive an annual influenza vaccine. Learn more.

Pay

SALARY RANGE: $139,220.00 - $184,460.00 Annually Salary ranges are shown for full-time jobs. If you're working part-time, your pay will be adjusted accordingly. This job is eligible for an incentive program. At CHOP, we are committed to fair and transparent pay practices. Factors such as skills and experience could result in an offer above the salary range noted in this job posting. Click here for more information regarding CHOP's Compensation and Benefits.