Data Analysis Post Bachelors Student

Data Analysis Post Bachelors Student Req.

Number:

IRC143942

Organization :

V-14/Test Engineering

City, State:

Los Alamos, New Mexico What You Will Do The Data Analysis Team within the Test Engineering group (V-14) seeks candidates with experience applying data-driven, computational, and analytical techniques to challenges in engineering and the physical sciences. Our mission is to organize and consolidate measured data and employ those data to provide accurate, timely, data-driven products in support of the annual assessment, stockpile modernization, and other national security missions. Examples of the work we do include, but are not limited to: Utilize efficient data processing and signal analysis techniques on large-scale, multimodal time series data (e.g., vibration, electromagnetic, and environmental) to rapidly detect and characterize signals of interest in support of national security missions, including weapons and nonproliferation efforts. Develop and implement statistical methods for engineering and scientific data like functional analysis of variance to provide real-time decisions with theoretical guarantees Apply data science and statistical principles to develop and evaluate a wide range of mathematical models, including generative, regression, and classification approaches in deep learning, as well as linear and other machine learning methods. Organize, label, and otherwise munge large sets of engineering data for preparation for subsequent analysis Monitor data collections from aircraft performing maneuvers to ensure collected data represent realistic weapons environments using informed engineering knowledge Our work integrates diverse theoretical disciplines, including data science, artificial intelligence, classical and Bayesian statistics, and mathematics, and applies them to complex physical systems in areas such as mechanical, electrical, and physical sciences. We seek candidates whose expertise and interests lie at the intersection of these fields and who are eager to contribute to cross-disciplinary research and innovation. Depending on the skills and interests of the selected candidate, they may contribute to any of the above example efforts, such as Data munging and exploratory analysis Implementing existing or developing new mathematical theory for an application Contributing to our collaborative code base of analysis tools Building advanced artificial intelligence models or pipelines (deep learning, machine learning, custom statistical models) Applying foundational engineering knowledge to provide informed decisions to stakeholders What You Need

Minimum Job Requirements:

Experience in both areas: An applied or natural science discipline such as engineering (mechanical, electrical, etc.), physics, or chemistry A computational or data-focused discipline such as computer science, data science, applied mathematics, or statistics This combination may be demonstrated through a double major (e.g., Mechanical Engineering and Statistics), a major-minor pairing, or a major in one field complemented by substantial experience-such as research, projects, or internships-in the other. Experience in data-scientific programming (e.g. MATLAB, Python, Julia, or R) Strong interpersonal, oral and written communication skills Demonstrated success working in an integrated team environment

Desired Qualifications:

Proficiency with object-oriented programming and version control systems (e.g. Git) Experience in data analysis, such as implementing mathematical/statistical models to time series data with fundamental understanding for how the models work analyzing experimental test data Experience in engineering, such as signal processing, including time and frequency domain analysis data acquisition, experimental test setup, and data collection modeling and simulation

Education:

A bachelor's degree in engineering, physics, applied mathematics, statistics, data science, or a related technical field earned within the past two years is required. For engineering degrees, graduation from an Accreditation Board for Engineering and Technology (ABET) accredited program is required.

Work Location:

The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management. Note to

Applicants:

Due to federal restrictions contained in the current National Defense Authorization Act, citizens of the People's Republic of China-including the special administrative regions of Hong Kong and Macau-as well as citizens of the Islamic Republic of Iran, the Democratic People's Republic of Korea (North Korea), and the Russian Federation, who are not Lawful Permanent Residents ("green card" holders) are prohibited from accessing facilities that support the mission, functions, and operations of national security laboratories and nuclear weapons production facilities, which includes Los Alamos National Laboratory. Applicants must submit a cover letter that addresses the key requirements of the position and outlines the applicant's interests

Clearance:

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 matter. •Eligibility requirements: To obtain a clearance, an individual must be at least 18 years of age; U.S. citizenship is required except in very limited circumstances. See DOE Order 472.2 for additional information Where You Will Work Located in beautiful northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security.

Our generous benefits package includes:

§ PPO or High Deductible medical insurance with the same large nationwide network § Dental and vision insurance § Free basic life and disability insurance § Paid childbirth and parental leave § Award-winning 401(k) (6% matching plus 3.5% annually) § Learning opportunities and tuition assistance § Flexible schedules and time off (PTO and holidays) § Onsite gyms and wellness programs § Extensive relocation packages (outside a 50 mile radius) Additional Details Directive 206.2 - Employment with Triad requires a favorable decision by NNSA indicating employee is suitable under NNSA Supplemental Directive 206.2. Please note that this requirement applies only to citizens of the United States. Foreign nationals are subject to a similar requirement under DOE Order 142.3A.

Clearance:

Q (Position will be cleared to this level). Selected applicants will be subject to a background investigation conducted by or on behalf of the Federal Government, and must meet eligibility requirements• for access to classified matter. This position requires a Q clearance. and obtaining such clearance requires US Citizenship except in extremely rare circumstances. Dependent upon the position, additional authorization to access classified information may be required, which may or may not be available to dual citizens. Receipt of a Q clearance and additional access authorization ultimately is a decision of the Federal Government and not of Triad. •Eligibility requirements: To obtain a clearance, an individual must be at least 18 years of age; U.S. citizenship is required except in very limited circumstances. See DOE Order 472.2 for additional information.

New-Employment Drug Test:

The Laboratory requires successful applicants to complete a new-employment drug test and maintains a substance abuse policy that includes random drug testing. Although New Mexico and other states have legalized the use of marijuana, use and possession of marijuana remain illegal under federal law. A positive drug test for marijuana will result in termination of employment, even if the use was pre-offer.

Internal Applicants:

Regular appointment employees who have served the required period of continuous service in their current position are eligible to apply for posted jobs throughout the Laboratory. If an employee has not served the required period of continuous service, they may only apply for Laboratory jobs with the documented approval of their Division Leader. Please refer to Policy Policy P701 for applicant eligibility requirements.