Simulation Data Scientist
Science and Technology on a Mission!
For more than 60 years, the Lawrence Livermore National Laboratory (LLNL) has applied science and technology to make the world a safer place.
We have an opening for a Simulation Data Scientist. You will work on an integrated team of software developers, researchers, and physicists, exploring and implementing data analytics for massively parallel scientific codes, running on the latest supercomputer architectures. This position is in the Applications, Simulations and Quality Division within the Computation Directorate matrixed to the Weapons and Complex Integration Principal Directorate.
Essential Duties
Create highly advanced software and algorithm solutions to meet the needs of new High Performance Computing (HPC) architectures.
Collaborate with scientists and researchers on data intensive applications, graph analysis, machine learning, statistical learning, information visualization, data integration, data streaming, scientific data mining, data fusion, programming models for scalable parallel computing, application performance modeling and analysis, scalable tool development, novel architectures, and/or HPC architecture simulation and evaluation.
Bring research results to practical use in institutional programs, while collaborating with scientists and application developers.
Provide solutions to complex technical problems that require in-depth analysis of multiple tangible and intangible factors and the creative use of innovative methods, while participating as a member of a multidisciplinary team and implementing scientific software.
Develop new ideas, modify approaches, and/or redefine customer requirements to address key HPC challenges in data science.
Direct multiple parallel tasks and priorities of customers and partners to ensure deadlines are met, while leveraging team members' skills to complete projects and tasks.
Perform other duties as assigned.
Qualifications
PhD in computer science or related field, or the equivalent combination of education and related experience.
Expert knowledge of HPC simulations, scientific data analysis, statistical analysis, knowledge discovery, large-scale data management, and/or big data technologies.
Substantial experience in of all aspects of the software project life cycle:
feasibility, requirements, design, implementation, integration, test and deployment.
Substantial experience developing software with C++, C, Java, Python, R, or Matlab, software applications in Linux, UNIX, data analysis algorithms, data management approaches, relational databases, or machine learning algorithms.
Advanced interpersonal skills necessary to interact with all levels of personnel, including senior management and sponsors across and external to the Laboratory.
Expert analytical, problem-solving, and decision-making skills to develop innovative solutions to complex problems.
Substantial experience in technical languages, concepts, or constructs and in one or more of the following advanced areas:
high performance computing, scientific data analysis, statistical analysis, knowledge discovery, systems programming, large-scale data management or big data technologies.
Expert verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information.
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 is a Career Indefinite position. Lab employees and external candidates may be considered for this position.
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 $1.5 billion, employing approximately 6,000 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.
. Apply now!Estimated Salary: $20 to $28 per hour based on qualifications.
For more than 60 years, the Lawrence Livermore National Laboratory (LLNL) has applied science and technology to make the world a safer place.
We have an opening for a Simulation Data Scientist. You will work on an integrated team of software developers, researchers, and physicists, exploring and implementing data analytics for massively parallel scientific codes, running on the latest supercomputer architectures. This position is in the Applications, Simulations and Quality Division within the Computation Directorate matrixed to the Weapons and Complex Integration Principal Directorate.
Essential Duties
Create highly advanced software and algorithm solutions to meet the needs of new High Performance Computing (HPC) architectures.
Collaborate with scientists and researchers on data intensive applications, graph analysis, machine learning, statistical learning, information visualization, data integration, data streaming, scientific data mining, data fusion, programming models for scalable parallel computing, application performance modeling and analysis, scalable tool development, novel architectures, and/or HPC architecture simulation and evaluation.
Bring research results to practical use in institutional programs, while collaborating with scientists and application developers.
Provide solutions to complex technical problems that require in-depth analysis of multiple tangible and intangible factors and the creative use of innovative methods, while participating as a member of a multidisciplinary team and implementing scientific software.
Develop new ideas, modify approaches, and/or redefine customer requirements to address key HPC challenges in data science.
Direct multiple parallel tasks and priorities of customers and partners to ensure deadlines are met, while leveraging team members' skills to complete projects and tasks.
Perform other duties as assigned.
Qualifications
PhD in computer science or related field, or the equivalent combination of education and related experience.
Expert knowledge of HPC simulations, scientific data analysis, statistical analysis, knowledge discovery, large-scale data management, and/or big data technologies.
Substantial experience in of all aspects of the software project life cycle:
feasibility, requirements, design, implementation, integration, test and deployment.
Substantial experience developing software with C++, C, Java, Python, R, or Matlab, software applications in Linux, UNIX, data analysis algorithms, data management approaches, relational databases, or machine learning algorithms.
Advanced interpersonal skills necessary to interact with all levels of personnel, including senior management and sponsors across and external to the Laboratory.
Expert analytical, problem-solving, and decision-making skills to develop innovative solutions to complex problems.
Substantial experience in technical languages, concepts, or constructs and in one or more of the following advanced areas:
high performance computing, scientific data analysis, statistical analysis, knowledge discovery, systems programming, large-scale data management or big data technologies.
Expert verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information.
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 is a Career Indefinite position. Lab employees and external candidates may be considered for this position.
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 $1.5 billion, employing approximately 6,000 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.
. Apply now!Estimated Salary: $20 to $28 per hour based on qualifications.
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