Please login/register to apply for this job.
27 Apr 2018

Full-Time Data Scientist @ Annapolis, Maryland, United States

The National Socio-Environmental Synthesis Center – Posted by sesync Annapolis, Maryland, United States

Job Description

The National Socio-Environmental Synthesis Center seeks a Data Scientist to join the cyberinfrastructure (CI) team in supporting collaborative, computational, and data-driven socio-environmental research. Our supported science teams and postdoctoral fellows come from many different disciplines and synthesize diverse models and data sets to answer large-scale questions at the intersection of humans and the environment. The Data Scientist will work closely with the CI team to assist scientists in performing data and model syntheses.
The Data Scientist’s typical activities include:
  • Advise on statistical approaches, design workflows, and prototype/optimize code;
  • Help researchers develop and use custom tools;
  • Assess and document project needs;
  • Teach in hands-on CI education workshops for students and researchers; and,
  • Assist researchers in making their data, code, analyses, and applications open, reproducible, and discoverable.
Candidates with experience in machine learning techniques, code optimization, and/or qualitative data analysis will be given priority consideration.
Why SESYNC:
SESYNC is dedicated to solving society’s most challenging and complex environmental problems by bringing together social, natural, and computational scientists to increase knowledge on the complex interactions between human and ecological systems. The computational requirements for conducting this research present many opportunities and challenges. Examples of the work we have supported include:
  • map and analyze a billion-point data set;
  • model shocks to the global food trade;
  • synthesize global biophysical and governance data on Marine Protected Areas;
  • develop R Shiny applications for targeted data exploration and cleaning;
  • monitor traffic pertaining to illegal wildlife trade through Google Trends data;
  • R packages: developed rslurm to facilitate High Performance Computing (HPC) pipelines and contributed major revisions to codyn to facilitate ecological community analysis
About our CI:
SESYNC’s CI is designed to enable mesoscale research, i.e., research that requires access to large data sets and processing resources but not necessarily traditional HPC. We embrace open source software to the fullest extent possible and support a variety of tools. Our CI staff consists of systems specialists, S-E researchers, and data scientists. All CI staff are encouraged to investigate new technologies they think may be useful or interesting in contributing to SESYNC’s mission.
Salary:
Commensurate with experience.
Required Qualifications:
  • Master’s degree +2 years’ experience or PhD in social, natural, computer or information science or engineering;
  • Experience writing code to process data and/or develop models in R, Python, or Matlab;
  • Demonstrated knowledge of basic descriptive and applied statistics;
  • Strong interpersonal and communication skills;
  • Interest in socio-environmental problems.
Desired Qualifications:
  • Knowledge of advanced statistical techniques (e.g., machine learning, SEM, Bayesian techniques, and/or econometric models) and appropriate applications;
  • Knowledge of and/or experience in environmental science or issues;
  • Experience working with spatial data/GIS;
  • Collaborative coding/version control tools;
  • Experience developing interactive visualizations or analysis tools (e.g., with Shiny) and/or using Jekyll

How to Apply

Using the webform, submit a cover letter, resume, and three professional references as a single PDF. You may include an optional URL to a project portfolio (e.g., your GitHub portfolio, professional website).
Position open until filled. For best consideration, please apply by May 25, 2018.

Job Categories: Data Scientist / Statistician. Job Types: Full-Time. Job Tags: bayesian, econometrics, machine learning, and r.

Job expires in 6 days.

Apply for this Job