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Associate Data Scientist

Apply now Job no: 502514
Work type: Staff
Location: Boston Main Campus
Categories: Information Technology Services

About Northeastern:

Founded in 1898, Northeastern is a global research university and a world leader in experiential learning. The same commitment to connecting with the world drives our use-inspired research enterprise. The university offers a comprehensive range of undergraduate and graduate programs leading to degrees through the doctorate in nine colleges and schools. Our campuses in Charlotte, N.C., San Francisco, Seattle, and Toronto are regional platforms for undergraduate and graduate learning and collaborative research. Northeastern pursues advanced research in security and materials at the Innovation Campus in Burlington, Massachusetts, and in coastal sustainability at the Marine Science Center in Nahant, Massachusetts.

 

About the Opportunity:

The Research Computing (RC) team at Northeastern University (NU) seeks a motivated, self-starting individual to be a member of our dynamic team as an Associate Data Scientist. The successful candidate will be a key link between the RC team and the research community at NU, including faculty and students across a broad range of departments, as well as outside users and partners, in order to help them understand and utilize RC resources for their research and teaching.

 

Responsibilities:

The Research Computing (RC) team at Northeastern University (NU) seeks a motivated, self-starting individual to be a member of our dynamic team as an Associate Data Scientist. The successful candidate will be a key link between the RC team and the research community at NU, including faculty and students across a broad range of departments, as well as outside users and partners, in order to help them understand and utilize RC resources for their research and teaching.

As an Associate Data Scientist at NU, your primary objective will be to support and enhance the research enterprise through direct interaction with faculty and students. A key function will be to assist research groups in taking full advantage of Discovery, NU’s rapidly evolving 1,700+ node HPC cluster installed at the Massachusetts Green High Performance Computing Center (MGHPCC). Support for code optimization and efficient use of scheduler features to maximize job throughput will be given through a combination of methods, including but not limited to consultations, training sessions, and written documentation. Guidance in the appropriate of application of statistical, computational, and visualization methods will be provided to NU faculty research groups in multiple scientific domains.  As a PhD level scientist, you will also participate in grant funding opportunities, and author research papers and presentations with faculty members at NU. The technical and scientific support provided by the Associate Data Scientist will be instrumental in helping optimize computational and data workflows, as well as improving research outcomes across the global university. 

The successful candidate that joins the rapidly growing NU RC team will have a unique opportunity to help shape the direction and development of new data analysis platforms.  These new tools, platforms, and long term data analysis and support strategies will have an immediate and lasting impact across the global university research community.

 

Qualifications:

  • Ph.D. in data science, mathematics, statistics, computer science or related fields. 
  • Strong and diversified experience in data analysis and visualization in particular with applications involving analysis of large and complex data sets, using machine learning and deep learning algorithms, as well as other advanced statistical procedures.
  • High proficiency in R, Python, and Python for research (e.g. NumPy, pandas, scikit-learn, Jupyter)
  • Strong programming skills involving distributed computing (such as Hadoop, Spark or other big data frameworks), Java, Json, and SAS.
  • High proficiency in the use of visualization tools (e.g. Tableau, PowerBI, Qlik)
  • Proficiency in statistical modeling, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms
  • Demonstrable interest in and experience with (digital) humanities or social sciences research is a plus
  • Proficiency working in Unix/Linux environments
  • Proficiency working with Git/Github
  • Experience with various database concepts (eg SQL, NoSQL, SPARQL, GraphDB)
  • Experience in a batch HPC environment with a parallel file system using Slurm
  • Experience in an academic or research community environment
  • Experience with scientific workflows
  • Excellent interpersonal communication skills
  • Ability to come up with solutions to loosely defined problems by leveraging pattern detection over potentially large datasets
  • Ability to understand and communicate statistical measures for interrogating the quality of data manipulation
  • Ability and willingness to learn new technologies and remain current in developing trends in the scientific computing community
  • Ability to communicate and document clearly
  • Demonstrated strong individual writing skills
  • Desire for continuous self-improvement and maintenance of skills through training
  • Curious by nature and unafraid of asking questions until you understand well-enough to teach someone else
  • Self-starter, with a proven track record for creativity and initiative
  • Able to prioritize multiple projects and work streams in a fast-paced environment

 


Preferred Qualifications:

  • 3+ years of relevant quantitative and qualitative research and analytics experience in an academic institution or industry research environment
  • Knowledge of technical standards for digital data curation, mapping, visualization, 3D modelling, web delivery and archiving tools is a plus
  • Knowledge of user interface design
  • Experience with cloud computing resources (such as AWS, Azure, GCP) is a plus
  • Experience with parallel programming paradigms, including but not limited to; MPI, OpenMP, and CUDA
  • Strong publication record consistent with a history of collaborative research in computational science or related field
  • Demonstrated commitment to Open Science through prior work with open source publishing, open data repositories, or equivalent

 

 

Salary Grade:

 12

Additional Information:

A criminal background check is required for this position.

Northeastern University is an equal opportunity employer, seeking to recruit and support a broadly diverse community of faculty and staff.  Northeastern values and celebrates diversity in all its forms and strives to foster an inclusive culture built on respect that affirms inter-group relations and builds cohesion. 

All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other  characteristic protected by applicable law.

To learn more about Northeastern University’s commitment and support of diversity and inclusion, please see www.northeastern.edu/diversity.

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