Biomedical Data Science Pathway

According to Forbes Magazine, “Data Scientist” is among the 10 highest paid job categories for 2015 with an estimated job growth for the sector of 15%.  Moreover, Glassdoor reports that not only are data scientists among the top 25 highest paying in-demand jobs, but those who work in the field have report the best working conditions and most job satisfaction of anyone in any job.  The NIH has developed a series of initiatives, the “Big Data to Knowledge (BD2K)” programs, to leverage the power of big data and informatics to understand biology and medicine.  Given this landscape, preparing a highly educated workforce to meet the demand for data scientists in biomedicine appears to be crucial and will provide trainees with myriad post-graduate options and opportunities. As the line between business and science blurs, PhDs are highly sought after as data scientists for their critical thinking and data skills. However, they need to master other technical skills beyond the bench. The URBEST Pathway can provide resources, support and partnerships for trainees to explore computational and data analytics technology in research activities in all areas of academic scholarship.

The Pathway is co-directed by by Dr. Helene McMurray, Assistant Professor of Clinical Pathology and Laboratory Medicine. Dr. McMurray regularly contributes her bioinformatics and genomics expertise to collaborative research projects with colleagues in biostatistics, neuroscience, and most recently, dermatology.

The Pathway is co-directed by Dr. Aslihan Ambeskovic, Head of Cancer Bioinformatics and Research Project Manager at Biomedical Genetics Department. Dr. Ambeskovic was an Insight Data Science Fellow in NYC as a postdoc, was hired as a Data Scientist at @Point of Care, and returned to UR as a cancer bioinformatician to apply her data science skills to cancer ‘omics. 

Discuss ideas you have about gaining experience in the Data Science Pathway with Dr. Helene McMurray and Dr. Aslihan Ambeskovic.

Explore the Data Science Pathway

• Learn more about the day-to-day of Data Science work through informational interviews with local data scientists, such as the members of the Center for Integrated Research Computing (CIRC), Department of Biostatistics and Computational Biology, Transcriptomics and Integrative Genomics Research Interest Group (TIGR) interest group, or the Rochester Informatics network. 
• Attend CIRC’s Winter Boot Camp or Summer or Summer School. These are hosted every year and registration is fast and furious with slots filling up quickly. If you miss registration, they also offer a monthly CIRC Symposium.
• Join the student-led Rochester Data Science Society.
• Learn a programming language through Code School or Codecademy.
• Apply to the Data Science Incubator Program or Insight Data Fellows Program. Both very-competitive programs are offered in several cities across America and include fully remote online options, too. 
• Take a certificate program, such as Johns Hopkins University’s Data Science Specialization through Coursera or UR’s Graduate Certificate of Advanced Study in Biomedical Data Science. 
• As a UR PhD graduate student, investigate the MS program in Data Science
• Explore Dr. Aslihan Ambeskovic’s suggested resources to prepare for a career in Data Science:
  • Stanford University’s CS229 Machine Learning
  • Harvard University’s CS109 Data Science
  • DataCamp’s Intro to Python For Data Science
  • Google for Education’s Python Class
  • SciPy 2013’s Scientific Computing with Python
  • Mode’s The SQL Tutorial for Data Analysis
  • NYC’s Open Data for All New Yorkers. You can find data science related projects and lots of data at this site.