Predictive Analytics Data Scientist

POSITION SUMMARY:

Enables comparative analyses and integration of large and complex data sets across multiple studies and sources. Responsibilities include interfacing with technology infrastructure to support biomedical research within the Heart Institute and the Department of Anesthesia. Outcomes from dedicated analytic projects should contribute to the growth and expansion of predictive analytics, heart institute and department of anesthesia on a local and national level. The data scientist should contribute to peer-reviewed journal publications, present at local and national conferences, identify funding opportunities, and assist with the development of contracts and grant proposals.

KEY ACCOUNTABILITIES:

1. Analysis and modeling of data for single and multi-center projects to make substantive contributions to the field of predictive analytics.
   
   
2. Engage in pre-processing of data (Extract-Transform-Load; ETL) to address missing data, potential noise/bias, and other unstructured data attributes.
3. Develop mathematical and machine learning models for prediction and classification of critical physiological events to efficiently and accurately describe potential associations that may exist within the data.
   
   
4. Analyze data using sophisticated data mining algorithms and methodologies to discover potential patterns and trends that may exist within the data.
5. Implement, deploy and monitor developed machine-based learning algorithms to examine streams of data using state of the art technologies.
   
   
6. Support to internal and external research proposals for regional and national funding agencies to contribute to sustainable research goals per JHACH strategic plans.
7. Advise on strategies for obtaining outside funds; works with Heart Institute and Department of Anesthesia staff to structure and propose new activities for funding; and prepare background materials as needed for meetings with foundations, government agencies and other donors. By year 3 this position should be self-sufficient based on grant awards.
   
   
8. Contribute to the initiatives related to the growth and sustainability of Heart Institute, Department of Anesthesia and predictive analytics at JHACH to facilitate research specific mission within the JHACH strategic plan. Namely, to contribute to aiding other faculty/fellows with grant awards and publications.
9. Remains informed and educated on industry trends, research findings, and evaluation methods.
   
   
10. Contributes to a motivated work environment by encouraging collaboration to achieve JHACH strategic goals.

QUALIFICATIONS:

• PhD in data science, analytics, informatics, statistics, mathematics, computer science, or related field.
  
  
• Minimum 3 years of experience with progressively complex data.
  
  
• Minimum of 3 years of experience with core analytic methodologies (e.g. regression, classification, clustering, matrix factorization, natural language processing, decision trees, support vector machines, neural networks).
  
  
• Strong programming skills in environments such as Python, Matlab, R, SQL or other interpreted developmental languages.
  
  

• Minimum of 3 years of exposure to development of machine learning algorithms and predictive modeling.
  
  
• Experience working with open source clinical data sources.
  
  
• Ability to communicate and relate well to people of diverse backgrounds, training and experience.
  
  

Please upload a CV and optional cover letter for consideration.

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristic. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors that are irrelevant to the program involved.

The successful candidate(s) for this position will be subject to a pre-employment background check.

If you are interested in applying for employment with The Johns Hopkins University and require special assistance or accommodation during any part of the pre-employment process, please contact the HR Business Services Office at jhurecruitment@jhu.edu. For TTY users, call via Maryland Relay or dial 711.

The following additional provisions may apply depending on which campus you will work. Your recruiter will advise accordingly.

During the Influenza ("the flu") season, as a condition of employment, The Johns Hopkins Institutions require all employees who provide ongoing services to patients or work in patient care or clinical care areas to have an annual influenza vaccination or possess an approved medical or religious exception. Failure to meet this requirement may result in termination of employment.

The pre-employment physical for positions in clinical areas, laboratories, working with research subjects, or involving community contact requires documentation of immune status against Rubella (German measles), Rubeola (Measles), Mumps, Varicella (chickenpox), Hepatitis B and documentation of having received the Tdap (Tetanus, diphtheria, pertussis) vaccination. This may include documentation of having two (2) MMR vaccines; two (2) Varicella vaccines; or antibody status to these diseases from laboratory testing. Blood tests for immunities to these diseases are ordinarily included in the pre-employment physical exam except for those employees who provide results of blood tests or immunization documentation from their own health care providers. Any vaccinations required for these diseases will be given at no cost in our Occupational Health office.

Equal Opportunity Employer
Note: Job Postings are updated daily and remain online until filled.

EEO is the Law
Learn more:
https://www1.eeoc.gov/employers/upload/eeoc_self_print_poster.pdf
Important legal information
http://hrnt.jhu.edu/legal.cfm