Lawrence Livermore National Laboratory

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Data Scientist

Location:  Livermore, CA
Category:  Science & Engineering
Organization:  Computation
Posting Requirement:  External w/ US Citizenship
Job ID: 102701
Job Code: Science & Engineering MTS 4 (SES.4) / Science & Engineering MTS 5 (SES.5)
Date Posted: August 25 2017

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Real Problems, Real Data! 
Imagine being part of an integrated team of researchers applying the power of extreme computing, data analytics and revolutionary sensor technologies to enable a new era of computational predictive biology.
Lawrence Livermore National Lab (LLNL) is engaged in efforts to develop and advance capability in computational predictive biology. A wide range of partners in this National initiative share a common vision and are working collaboratively to enable a revolutionary approach to improve cancer science, detect and mitigate biological threats and improve biological understanding through the integration of sensors and experiments, cutting-edge computational simulations, large-scale statistical analysis tools, and bioscience based theory and algorithm development.

We currently have an opening for a Data Scientist. You will be part of a team which develops a unified computational and data space that more tightly weaves together biological sensors and experiments, cutting-edge computational simulations, large-scale statistical analysis tools, and bioscience-based theory and algorithm development.

This position will be filled at either the SES.4 or SES.5 level, depending on your qualifications. Additional job responsibilities (outlined below) will be assigned if you are selected at the higher level.

Essential Duties
- Provide technical leadership with scientists and researchers in one or more of the following areas: data intensive applications, text processing, graph analysis, machine learning, statistical learning, information visualization, low-level data management, data integration, data streaming, scientific data mining, data fusion, massive-scale knowledge fusion using semantic graphs, database technology, programming models for scalable parallel computing, application performance modeling and analysis, scalable tool development, novel architectures (e.g., FPGAs, GPUs and embedded systems), and HPC architecture simulation and evaluation.
- Lead the development of advanced algorithms in support of the above R&D efforts.
- Lead a team of researchers to produce high-quality deliverables and publish and present research results in peer-reviewed publications and at scientific conferences.
- Set broad research and project vision with LLNL scientists and application developers to bring research results to practical use in LLNL Global Security programs.
- Assess the requirements for data sciences research from LLNL programs and external government sponsors.
- Perform advanced development of data analysis algorithms to address program and sponsor data sciences requirements.
- Perform other duties as assigned.
Additional Duties at the SES.5 Level
- Champion strategic technical decisions made by senior management and external customers.
- Serve as a mentor across the organization in the area of Data Sciences.
- Serve as organization spokesperson by Laboratory management and/or external advisor by sponsors.

- Master’s degree in Engineering, Computer Science, Applied Statistics, Applied Mathematics, Computational Biology, or a related field, or the equivalent combination of education and related experience.
- Subject matter expert knowledge and significant experience in Data Science including significant experience in algorithm development.
- Significant experience leading complex project with responsibility for budgets, schedules, and deliverables; experience with project management and resource allocation.
- Significant experience providing expert level technical leadership for machine learning and statistical analysis projects and providing solutions to highly complex problems.
- Significant experience with one or more higher-level programming languages such as C/C++, Java/Scala, or Python.
- Experience with one or more scientific analysis and prototyping environments such as R, MATLAB, or the SciPy Stack.
- Demonstrated proficient verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information.
Additional Qualifications at the SES.5 Level
- PhD in Engineering, Computer Science, Applied Statistics, Applied Mathematics, Computational Biology or related field.
- Nationally recognized expert in data science.
- Extensive experience and demonstrated ability to lead and develop positions on cutting-edge technologies.

Pre-Employment Drug Test:  External applicant(s) selected for this position will be required to pass a post-offer, pre-employment drug test.

Anticipated Clearance Level:  Q (Position will be cleared to this level). Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified information or matter. In addition, all L or Q cleared employees are subject to random drug testing.  If you hold multiple citizenships (U.S. and another country), you may be required to renounce your non-U.S. citizenship before a DOE L or Q clearance will be processed/granted.


Note:  This listing has multiple openings; these are Career Indefinite positions.  Lab employees and external candidates may be considered for these positions.

About Us

Lawrence Livermore National Laboratory (LLNL), located in the San Francisco Bay Area (East Bay), is a premier applied science laboratory that is part of the National Nuclear Security Administration (NNSA) within the Department of Energy (DOE). LLNL's mission is strengthening national security by developing and applying cutting-edge science, technology, and engineering that respond with vision, quality, integrity, and technical excellence to scientific issues of national importance. The Laboratory has a current annual budget of about $1.8 billion, employing approximately 6,500 employees.

LLNL is an affirmative action/ equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, protected veteran status, age, citizenship, or any other characteristic protected by law.

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