Senior Data Scientist

The Aerospace Corporation•El Segundo, CA

1d•Hybrid

About The Position

The Aerospace Corporation is the trusted partner to the nation’s space programs, solving the hardest problems and providing unmatched technical expertise. As the operator of a federally funded research and development center (FFRDC), we are broadly engaged across all aspects of space— delivering innovative solutions that span satellite, launch, ground, and cyber systems for defense, civil and commercial customers. When you join our team, you’ll be part of a special collection of problem solvers, thought leaders, and innovators. Join us and take your place in space. Information Systems and Cyber Division (ISCD) staff couple the latest in information system technologies, such as elastic compute clouds, containerization, microservices, real-time operating systems, and visualization frameworks, with expertise in cyber security, software architecture, software engineering, data science, Artificial Intelligence, process improvement, and software development to deliver responsive, resilient, high-performance software intensive systems to our Intelligence Community, DoD, and civilian customers. The Data Science and Artificial Intelligence Department (DSAID) provides expertise and delivers customer solutions. DSAID seeks a creative and enthusiastic Data Scientist to join a diverse team of engineers, data scientists, and programmers with a passion for researching, prototyping, understanding, building AI and data enabled tools across the space enterprise. The Senior Data Scientist position focuses on transforming complex business challenges into practical analytical solutions using statistical modeling, machine learning algorithms, simulation techniques, and optimization strategies for clients in the national defense and civil space sectors. The role involves partnering with engineering teams to deploy scalable solutions that power customer-facing applications. Key responsibilities include developing sophisticated analytical models by leveraging expertise in databases, cloud infrastructure, MLOps practices, and programming. The position also contributes to the broader data science team by enhancing internal tools and expanding the shared library of packages and applications. Additionally, the role requires collaboration with model risk management teams to ensure thorough validation of model accuracy and reliability before production deployment.

Requirements

Bachelor of Science degree in STEM or a technical field
6 or more years of professional experience as a data scientist, machine learning engineer, or AI/ML researcher in any domain
Demonstrated ability with applied AI to Defense or Intelligence Community domains
Software development skills including familiarity with machine learning and deep learning libraries in Python
Experience with and understanding of machine learning and artificial intelligence, software engineering, and statistics
Proven ability to take initiative and successfully completing tasks, leading complex technical projects, and collaborating effectively.
Ability to obtain and maintain a security clearance, which is issued by the US government.
U.S citizenship is required to obtain a security clearance
Bachelor of Science degree in a technical field, or a bachelor’s degree and equivalent technical experience
10 or more years of professional experience as a data scientist, machine learning engineer, or AI/ML researcher in any domain
Demonstrated ability with technical development and leading development teams in applied AI to Defense or Intelligence Community domains
Demonstrated ability in software engineering concepts (algorithms, data structures, DevOps, version control, coding standards, etc.)
Demonstrated ability in working with customers and translating non-technical functionality into technical requirements

Nice To Haves

Advanced degree in computer science, data analytics, information systems or closely related field
Experience in leading large sets of diverse teams to accomplish difficult applied AI goals in the DoD enterprise
Demonstrated ability to efficiently deliver analysis and insights using compelling data visualizations to broad audiences from data that is often large, unstructured, or unprocessed
Experience in software engineering and machine learning development best practices (e.g. code, model, and data set version control, experiment tracking and reproduction)
Demonstrated contributions to open-source software repositories (github, kaggle, etc.)
Experience with containerization platforms (Docker, Kubernetes) and deploying ML models within applications or on cloud platforms (AWS, Azure, etc.)
Active security clearance

Responsibilities

Advising, prototyping, and integrating data science and AI technologies.
Establishing and maintaining strategic partnerships with key stakeholders
Working on teams spanning various disciplines, experience levels, and organizational boundaries.
Spearheading cutting-edge applied research and development efforts
Helping to shape AI strategy, roadmaps, research priorities, and investment decisions
Evaluating technologies and data science models for use in scalable and resilient mission-critical applications
Building and leading innovative teams to develop ML algorithms and application prototypes
Presenting written and verbal results to customer stakeholders and the larger aerospace community
Reinforcing an environment of learning and progress with team members and colleagues
Mentoring team members
Committing to ongoing learning
Maintaining current working knowledge in data science and AI as well as foundational skills in relevant domains, such as physics, math, and/or software engineering
Developing a deep understanding of government systems and government missions.
Transforming complex business challenges into practical analytical solutions using statistical modeling, machine learning algorithms, simulation techniques, and optimization strategies.
Partnering with engineering teams to deploy scalable solutions that power customer-facing applications.
Developing sophisticated analytical models by leveraging expertise in databases, cloud infrastructure, MLOps practices, and programming.
Enhancing internal tools and expanding the shared library of packages and applications.
Collaborating with model risk management teams to ensure thorough validation of model accuracy and reliability before production deployment.

Benefits

Comprehensive health care and wellness plans
Paid holidays, sick time, and vacation
Standard and alternate work schedules, including telework options
401(k) Plan — Employees receive a total company-paid benefit of 8%, 10%, or 12% of eligible compensation based on years of service and matching contributions; employees are immediately eligible and vested in the plan upon hire
Flexible spending accounts
Variable pay program for exceptional contributions
Relocation assistance
Professional growth and development programs to help advance your career
Education assistance programs
An inclusive work environment built on teamwork, flexibility, and respect