Data Scientist

Additional job responsibilities, at the SES.2 level

• Contribute to multiple parallel tasks and priorities of customers and partners, ensuring deadlines are met.
• Solve abstract problems, converting them into useable algorithms and software modules.
• Provide solutions that require analysis of multiple factors and the creative use of established methods.
• Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
• Bachelor’s degree in data science, computer science, mathematics, statistics, or related technical field, or the equivalent combination of education and related experience.
• Fundamental knowledge of one or more of the following: scientific data analysis, statistical analysis, knowledge discovery, supervised learning, unsupervised learning, deep learning, reinforcement learning, natural language processing, and big data technologies.
• Knowledge of adversarial AI methods, including evasion attacks, privacy attacks, and data poisoning attacks.
• Skilled in all aspects of the data science life cycle: feasibility / background research, data exploration, feature engineering, modeling, visualization, deployment.
• Fundamental experience developing data science algorithms with C++, Python, or R in Linux, UNIX, Windows environments, sufficient to integrate solutions into larger applications.
• Experience developing extensible and maintainable software leveraging software design principles.
• Experience with scikit-learn, PyTorch, TensorFlow, or similar machine learning (AI/ML) development API for the purpose of developing data science solutions.
• Ability to effectively handle concurrent technical tasks with conflicting priorities, to approach difficult problems with enthusiasm and creativity and to change focus when necessary, and to work independently and implement research concepts in a multi-disciplinary team environment, where commitments and deadlines are important to project success.
• Sufficient interpersonal skills necessary to interact with all levels of personnel.
• Sufficient verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information.

Additional qualifications at the SES.2 level

• Comprehensive analytical, problem-solving, and decision-making skills to develop creative solutions to complex problems.
• Broad experience with one or more of the following technical languages, concepts, or constructs: Python, scientific data analysis, statistical analysis, knowledge discovery, supervised learning, unsupervised learning, deep learning, reinforcement learning, natural language processing, and big data technologies.
• Proficient experience with at least one of the following advanced ML concepts: Transfer Learning, distributed ML (data/model), ML operations, generative models, Bayesian optimization, computer vision modeling, transformers, graph neural networks, uncertainty quantification, surrogate modeling, or techniques for data-poor ML (low-shot, coresets, etc.).

Pay Range

• $121,830 - $185,544 Annually
• $121,830 - $154,500 Annually for the SES.1 level
• $146,340 - $185,544 Annually for the SES.2 level
• This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.
• #LI-Hybrid

Position Information

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Security Clearance

Pre-Employment Drug Test

Wireless and Medical Devices

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Equal Employment Opportunity

Reasonable Accommodation

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