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Supervisor of Applied Data Science

Date: Aug 8, 2017

Location: Philadelphia, PA, US, 19146

Company: CHOP

Job Description

Req ID: 12685

Shift: Days

Employment Status: AF - Active - Regular - Full Time 

Job Summary

The Children’s Hospital Of Philadelphia (CHOP) Research Institute is recruiting a new team to build a data and informatics program called “Arcus” that will link clinical and biological data and provide world-class computational tools to solve the most challenging problems in child health.   Recognizing the central role of data to the future of pediatric research, CHOP leadership and the Board of Directors committed to a funding plan, and Arcus was launched in July 2017.  The Arcus team integrates with major scientific initiatives in the Research Institute Strategic Plan: Lifespan, Rare Diseases, Novel Devices and Therapeutics, and Precision Health.  We seek mission-oriented professionals with interest and expertise in the areas of biomedical science, library science, data education, data science, cloud computing, data privacy, and security.

The Supervisor of Applied Data Science (ADS) at the Children’s Hospital of Philadelphia Research Institute will build and lead the Arcus Applied Data Science team and contribute to all data science activities for the Arcus program. In concert with the Director of Applied Data Science and key stakeholders in the Research Institute, the Supervisor of Applied Data Science will be responsible for the identification and execution of data engineering projects that facilitate increased utility of data and analytic tools in Arcus that address well-defined, high-priority scientific needs within the CHOP research community. This may include, but is not limited to, efforts that provide feature extraction from unstructured data, information query and retrieval, data annotation and linking, data management, and standardized biomedical data science research pipelines. The Supervisor of ADS will promote the application of Arcus data science capabilities and foster collaboration between data scientists and biomedical researchers within the CHOP community through direct support to existing biomedical research projects and consultation on biomedical research funding proposals. In support of the Arcus Education Group, the Supervisor of ADS will contribute to endeavors that raise awareness and understanding of data science methods and the Arcus platform among biomedical researchers. The successful candidate will have experience recruiting and managing a data science team, a proven track record of executing data science projects with clearly defined scope and organizational impact, and demonstrated ability to work in a highly interdisciplinary, dynamic environment. This individual should have a “right tool for the right job” philosophy and must be able to work with biomedical researchers to identify data science requirements that demonstrably address specific biomedical research limitations. Most of all, we are looking for someone who shares our vision to exponentially improve child health and scientific knowledge through the integration and expansion of data science within biomedical research.

Job Responsibilities

1. Recruits, hires, and manages a team of staff scientists in the development and execution of a high-impact applied data science program.
2. Serves as the subject matter expert and lead architect in the development of high-quality software implementing models and algorithms as application programming interfaces or other service-oriented software implementations.
3. Serves as the subject matter expert in the assessment and implementation of computational algorithms for data engineering and analysis efforts.
4. Manage complex data science analysis and engineering projects and take responsibility for major components of larger programs; assign work to junior staff, identifying, tracking, and reporting on tasks and deliverables against project timelines.
5. Collaborate with clinical and biomedical researchers to identify opportunities where data science can support clinical and translational research.
6. Contributes to planning and writing of biomedical research funding proposals that require data science support.
7. Disseminates research findings through peer reviewed journal articles and professional conference presentations.
8. Communicates methods, implementation, and results to varied audience of clinicians, scientists, analysts, and programmers.
9. Provides data science guidance and mentorship to biomedical researcher collaborators, junior staff, students and research trainees (medical fellows, post-docs).
10. Sets standards and holds staff accountable for the formulation of analysis plans that meet stringent criteria for reproducibility and measures of significance. 
11. Play a lead role in educating a varied audience of clinicians, scientists, analysts, and programmers on data science methods, implementation, and results.


Required Education and Experience

1. PhD required in Analytics, Data Science, Statistics, Mathematics, Computer Science or a related field. Alternately equivalent experience in data analysis and predictive modeling will be considered in lieu of relevant degree. 
2. Seven to twelve years of experience with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects.
3. Zero to three years experience building and managing a technical or scientific team.
4. Expertise and demonstrated ability at acquiring new technical/analytic skills and domain knowledge to support successful contribution to research and development projects is required.
5. Expertise formulating analysis plans and selecting appropriate methods is required.
6. Expertise using existing machine learning and analytic tools such as  ScikitLearn, Weka, R, and Mathematica in either applied academic or professional projects is required.
7. Expertise writing code in applied academic or professional projects using one or more of the following languages: Python, Scala, Java is required.
8. Familiarity with relational databases (e.g. Postgres, MySQL) strongly preferred.
9. Familiarity RESTful web services application programming interfaces preferred.
10. Strong verbal and written communications skills with the demonstrated ability to explain complex technical concepts to a lay audience.
11. Applied statistics or mathematical modeling experience required.
12. Natural language processing experience particularly in the biological and medical domains preferred.
13. Experience using distributed computing technologies (e.g. Akka, MapReduce, Cuda) preferred.
14. Familiarity with graph, key value, and document data stores (e.g. Neo4j, Hadoop, MongoDB) preferred.
15. Experience creating informative visualizations for complex, high dimensional data preferred.
16. Experience with probabilistic graphical models, time series predictive models, Markov models preferred.

Nearest Major Market: Philadelphia

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