Data Scientist II-Data Driven Discovery in Biomedicine (D3b)

Children's Hospital of Philadelphia•Philadelphia, PA

4d•Onsite

About The Position

Perform exploratory data analysis and predictive modeling in pediatric biomedical research using machine learning, statistical, and mathematical analysis incorporating heterogeneous and complex data types independently based on milestone assignments from senior staff. Contribute to assessing and implementing computational, algorithmic, and predictive analytics approaches to address assigned biomedical research questions in areas such as clinical decision support and population health surveillance. Contribute to the experimental design, execution, test and critical evaluation of methods as applied to translational data science research projects. Use a flexible, analytical approach to extract optimal value from biomedical data. Contribute to design and conduct of continuous validation plans for production systems that incorporate models and algorithms, providing guidelines and support for large-scale implementation. Contribute to the creation, adoption, and adherence to best practice methodologies for performing data analysis and predictive modeling experiments.

Requirements

Bachelor's Degree in analytics, computer/data science, statistics, mathematics or related field
At least three (3) years of applied algorithm development, data science, applied statistics, machine learning, or mathematical modeling projects experience
Intermediate proficiency with formulating analysis plans and selecting appropriate methods
Intermediate proficiency with machine learning and analytic tools (ScikitLearn, Weka, R, and Mathematica)
Intermediate proficiency with programing languages (Python, Scala, Java)
Intermediate proficiency with writing code in applied academic or professional projects
Intermediate proficiency with distributed computing technologies (Akka, MapReduce, Cuda)
Intermediate proficiency with creating informative visualizations for complex, high dimensional data
Intermediate proficiency with probabilistic graphical, time series predictive, statistical/mathematical and Markov models
Substantial knowledge of relational databases (Postgres, MySQL)
Substantial knowledge of web services application programming interfaces
Substantial knowledge of biological and medical domains
Substantial knowledge of graph, key value, and document data stores (Neo4j, Hadoop, MongoDB)
Excellent verbal and written communications skills
Ability to maintain confidentiality and professionalism
Ability to work independently with minimal supervision
Ability to gather, analyze and make recommendations/decisions based on data / best practices
Ability to convey complex or technical information in an easy-to-understand manner
Ability to collaborate with stakeholders at all levels

Nice To Haves

At least five (5) years with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects experience

Responsibilities

Implement computational algorithms and experiments for test and evaluation; interprets data to assess algorithm performance.
Make significant contributions to the formulation of analysis plans and associated documentation of methods that meet stringent criteria for reproducibility and measures of significance.
Develop high-quality code implementing models and algorithms as application programming interfaces or other service-oriented software implementations.
Participate in communication of research methods, implementation, and results to varied audience of clinicians, scientists, analysts, and programmers.
Work closely with applications research group to translate models and algorithms into engineered production applications.
Contribute to manuscript writing for results publication, authors abstracts, and presents at professional conferences.