Data Scientist II

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

We’re seeking breakthrough makers! Children’s Hospital of Philadelphia was built on the belief that we can change lives. Today, in every role throughout our hospital, research institute and care network, the 22,000 members of our workforce are finding new ways – big and small – to make a difference for the patients and families we serve.

If you are ready to challenge yourself, be inspired and grow – no matter what your role – you just may be the kind of breakthrough maker who will thrive at CHOP.

Job Summary

• 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.

Job 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.

Job Responsibilities (Continued)

•  Primary responsibility will be to partner with key stakeholders and lead analysis to support and enable the continued capacity planning that is critical to CHOP’s Capacity Management.
• Leverage data to drive decisions and introduce automation, predictability & optimization to allow us to operate efficiently and reliably at scale.
• Identify business problems and solve them by using various numerical techniques, algorithms, and models in Operations, Data Science, and Data Mining.
• Design and develop advanced mathematical, optimization models and apply them to define strategic and tactical needs and drive the appropriate business and technical solutions in the areas of Capacity Planning, Staffing, Supply Chain, Process Design & Optimization and Demand Forecasting.
• Research, prototype and experiment with models by using modeling languages such as Python, MATLAB, Mosel or R; participate in the production level deployment.
• Create, enhance, and maintain technical documentation, and present.
• Influence organization's long-term roadmap and partner in onboarding new technologies onto team's toolbox.
• The ideal candidate will have a passion for creating impact from the ground up in a fast-paced environment. Additionally, you will have a proven track record of thought leadership and impact in developing similar analytics and metrics-based programs

Job Responsibilities (Continued)

The department works approximately 80% remotely, 20% on-site and/or on an as needed basis to achieve departmental goals and fulfill job responsibilities.

Required Education and Experience

• Required Education: Bachelors in Analytics, Data Science, Statistics, Mathematics, Computer Science or a related field.
• Required Experience: At least three (3) years of experience with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects.
• Preferred Education, Experience & Cert/Lic
• Preferred Education: Masters in Analytics, Data Science, Statistics, Mathematics, Computer Science or a related field. Non-degree graduate coursework such as a graduate certificate in Analytics, Statistics, or Data Science.
• Preferred Experience: Four (4) or more years of experience with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects.

Additional Technical Requirements

• Experience and demonstrated ability acquiring new technical/analytic skills and domain knowledge to support successful contribution to research and development projects is required.
• Experience formulating or contributing to the formulation of analysis plans and selection of appropriate methods.
• Experience using existing machine learning and analytic tools such as ScikitLearn, Weka, R, and Mathematica in either applied educational or professional projects is required.
• Experience writing code in either applied educational 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 preferred.
• 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.

Department Specific Additional Technical Requirements:

•  At least three (3) years of applied Machine Learning expertise
• At least three (3) years experience in building models, new frameworks and developing algorithms for statistical modeling, mathematical programming (OR) and simulation in industry and/or academia
• At least three (3) years experience in modeling and analyzing large-scale structured and unstructured data using Python or R
• At least three (3) years experience with algorithms and optimizations
• At least three (3) years experience in SQL and data modeling
• Knowledge of Statistics & Probability (e.g. Hypothesis testing, Regression, Stochastic modeling, Markov Chains etc.)
• Experience writing testable code and shipping code into production
• Experience in languages SQL and Python