NET ESolutions is seeking an experienced data scientist/analytics professional to lead development and analytical efforts related to the National Institutes of Health's (NIH's) biomedical research portfolio. Specific examples of tasks that have actually been performed by data scientists/analytics professionals at NETE include:
- Research/learn and utilize probabilistic topic models (e.g, Latent Dirichlet Allocation) and text mining to identify research trends, gaps in funding for various conditions/diseases, and duplication of effort across the NIH and its funded organizations.
- Support pan-Federal biomedical research data warehouse design by applying decision analysis to help select database architectures and identify KPIs.
- Advise internal software development staff on analytics dashboard layout for their various products. Key areas are (a) what functions to provide and their value, (2) data visualizations and key statistics to support NIH decisionmaking.
- Serve as primary statistical and analytics consultant within NETE, helping solve key analytics challenges on several health/biomedical-research related projects.
- Maintain knowledge of project-relevant research and available software (proprietary and open-source) and communicate findings to team as appropriate.
Key candidate qualities:
- Superb presentation skills - most communications happen via WebEX-type teleconferences (some are in person too), so ability to communicate complex ideas in an engaging manner using PowerPoint to a remote, non-technical audience is essential.
- Particular emphasis will be on ability to develop informative visualizations of key ideas and on the ability to speak clearly and effectively.
- Strong interest in and ability to program with a variety of programming languages. In particular, a working knowledge of R, Python, Java and C/C++ is preferred, as these are the languages that our current data science prototypes utilize. By working knowledge, we mean the ability to research, write, test, and deploy software prototypes with minimal guidance - you will be expected to select and test the correctness of your algorithms and to be able to modify the design upon request.
- Knowledge of enterprise-level software design and deployment is not expected or required. We have an entire integration team that will assist with deployment; however, you will be heavily involved in the process to ensure continuity of software functionality.
- Strong background in applied mathematics, with emphasis on probability models, statistical inference, and machine/statistical learning (on the level of Introduction to Statistical Learning by James, Witten, Hastie and Tibshirani).
- A particular need, and a huge plus, would be substantial familiarity with text mining. The vast majority of the data streams we deal with are text-based, so skills in this area will be highly valued.
- Knowledge of statistical inference should include a working knowledge of classical, likelihood, and Bayesian modeling approaches, as well as ability to implement basic bootstrap inference and non-parametric tests (e.g., permutation tests).
- Independent -- ability to operate independently, including researching, developing, and discussing possible solutions with team members. There will be very limited technical guidance and oversight of this role - you will be expected to serve as the subject matter expert and internal consultant in the analytics/data science arena.
Qualifications:
- Masters degree in an appropriate quantitative discipline: statistics, applied mathematics, engineering, operations research/management science, physics with at least two semester-long courses covering at least one general-purpose programming language -- examples include, but are not limited to, C/C++, Java, C#, Python, Ruby, Scala, Haskell, etc.
- MATLAB, computer algebra systems, R, SAS, SAP, VBA, and other domain-specific application-specific languages are not acceptable substitutes.
- 5+ years performing data science and analytics. This should include substantial experience in presenting analytical results to non-technical audiences and a high degree of client interaction.
- Demonstrated knowledge and use of R or Python and C/C++ or Java in data science applications is essential - prototyping is a major part of this role.
- Ability to pass a government background check.
Please contact me at mike@nete.com if interested.
------------------------------
Michael Beyer PE,CAP
Princiapl Data Scientist
------------------------------