Data Scientist 2

United Launch Alliance•Centennial, CO

1d•$92,783 - $154,638

About The Position

The Data Scientist 2 provides enterprise-level data analytics and data science support within the Systems Engineering organization. The role interprets data, analyzes results using statistical techniques, and develops reports, presentations, and technical documents. It designs, builds, tests, evaluates, and implements models using diverse datasets to address problems across the company, and develops visualizations of datasets and modeling results. The position communicates findings to engineers, leadership, and technical and non-technical stakeholders, and collaborates across the enterprise to develop tools and methods for analyses. It contributes to continuous improvement of the tools and processes used in its work and participates in multidisciplinary teams assessing customer and operational needs and developing solutions for decision-making across engineering, manufacturing, launch operations, and business disciplines. The candidate scales data science activities to fit project needs. The role is based in Denver, requires 10% travel, and relocation may be available. This position requires applicants to be U.S. Persons under ITAR.

Requirements

Bachelor’s degree in Engineering, Data Science or Analytics, Statistics, Applied Mathematics, or a related field.
At least 2 years of experience emphasizing Data Analytics/Data Science.
Technical expertise in data models, data mining, data extraction, and data-wrangling techniques.
Strong knowledge of and experience using statistical or analytical packages for small and big data, such as Python, R, and/or MATLAB, and using them to provide business insights.
Experience applying machine learning and/or artificial intelligence to business or engineering applications.
Strong analytical skills, including the ability to collect, organize, analyze, and disseminate significant amounts of information accurately and with attention to detail.
Ability to query data, write reports, and present findings.
Ability to operate independently and work as part of a team.
Excellent written and oral communication and organization skills to maintain focus and achieve consensus within diverse multidisciplinary teams.
Ability to work autonomously, learn and execute processes, and perform collaboratively.
Must be a U.S. Person as defined by ITAR.

Nice To Haves

Master’s degree in Engineering, Data Science or Analytics, Statistics, Applied Mathematics, or a related field.
Experience in the aerospace industry with existing and evolving launch systems or satellite systems.
Experience with multidisciplinary teams resolving technical and programmatic issues using current or advanced statistical and data science techniques.
Knowledge of both engineering and statistics/data science.
Experience with cloud-based analysis or modeling, such as AWS, Azure, or GCS.
Basic understanding of launch vehicles.
Self-motivation and demonstrated initiative, teamwork, and leadership on previous technical projects.
Demonstrated data analytics experience in an aerospace environment.
Technical knowledge supporting launch vehicle and/or satellite vehicle design, analysis, production, and operations.

Responsibilities

Interpret data and analyze results using statistical techniques; provide reports, presentations, and technical documents as required.
Design, analyze, build, test, evaluate, and implement models from diverse datasets to solve company problems.
Develop visualizations of datasets under investigation and modeling results.
Communicate findings verbally and through reports or presentations to engineers, leadership, and technical and non-technical stakeholders.
Work with individuals across the enterprise to develop appropriate tools and methods for analyses.
Help continuously improve the tools and processes used to execute the data science function.
Participate in multidisciplinary project teams to evaluate customer and operational needs and develop solutions to support decision-making across engineering, manufacturing, launch operations, and business disciplines.
Identify and apply an appropriate scale of data science activities for specific project needs.