Data Scientist Asc - E1

Lockheed Martin; Marietta (GA); On-site; USD 67,000 - 124,000; Full time

Benefits offered by this job

Medical benefits

Dental & Vision

Flexible work arrangements

401(k) match

Paid time off

Holidays

Parental Leave

Education Assistance

Life Insurance

Disability insurance

Job summary

Lockheed Martin is seeking a data science researcher to perform exploratory analysis on large datasets, develop predictive models, and apply AI/ML techniques to extract actionable insights for decision making. The role involves working with statistics, NLP/ML methods, visualization, and collaborating with cross‑functional teams in a high‑impact aerospace environment.

The candidate should have a strong foundation in applied statistics and machine learning, plus knowledge of software development

Qualifications

• Bachelors degree in Engineering, Physics, Computer Science, Software, Data Science, Data Analysis, Physics, Mathematics or equivalent experience/combined education.
• Knowledge of AI/ML fundamentals.
• Understanding of software development practices – style enforcement, standard testing, software quality, code reviews, etc.

Skills

AI/ML fundamentals

Education

Bachelor's degree in Engineering, Physics, Computer Science, Software, Data Science, Data Analysis, Physics, Mathematics or equivalent experience/combined education

Degree in Data Science

Tools

SAS

Python

Git

Job description

Standard Job Description

Perform exploratory research and analysis to identify novel and meaningful patterns in data and uses statistical methods to reject or accept proposed hypotheses about relationships or latent predictive factors discovered through their work to provide business value. Uses a combination of tools, technologies, and numerical computing systems (i.e.: GPU processing, distributed computing, highly parallel coding, cloud computing, machine learning, visualization, system modelling and simulation) to achieve results. Areas of expertise should include several of the following: applied statistics, text mining, natural language processing, deep learning, optimization, and other similar fields. Work on datasets with applied statistics and machine learning algorithms; Use exploratory data analysis techniques to identify meaningful relationships, patterns, or trends from complex data sets and discover opportunities in datasets to support decision-making; Develop predictive models and new algorithms to solve data / business problems; Understand the math and statistics behind the models and interpret, extrapolate, and prescribe from data to deliver actionable recommendations using effective visualizations

Standard Job Description

Perform exploratory research and analysis to identify novel and meaningful patterns in data and uses statistical methods to reject or accept proposed hypotheses about relationships or latent predictive factors discovered through their work to provide business value. Uses a combination of tools, technologies, and numerical computing systems (i.e.: GPU processing, distributed computing, highly parallel coding, cloud computing, machine learning, visualization, system modelling and simulation) to achieve results. Areas of expertise should include several of the following: applied statistics, text mining, natural language processing, deep learning, optimization, and other similar fields. Work on datasets with applied statistics and machine learning algorithms; Use exploratory data analysis techniques to identify meaningful relationships, patterns, or trends from complex data sets and discover opportunities in datasets to support decision-making; Develop predictive models and new algorithms to solve data / business problems; Understand the math and statistics behind the models and interpret, extrapolate, and prescribe from data to deliver actionable recommendations using effective visualizations

Basic Qualifications

• Bachelors degree in Engineering, Physics, Computer Science, Software, Data Science, Data Analysis, Physics, Mathematics or equivalent experience/combined education.
• Knowledge of AI/ML fundamentals
• Understanding of software development practices – style enforcement, standard testing, software quality, code reviews, etc.

Desired Skills

• Knowledge of Defence Air System Supply and Maintenance networks and systems
• SAS, Python, Git Experience
• Degree in Data Science
• Strong communication and organizational skills

Pay Information

Full-Time Salary Range: $67000.00 - $124400.00

At Lockheed Martin, we know mission success starts with taking care of our people. Our Total Rewards program is designed to attract top talent, support your well-being, and help you grow—both professionally and personally.

The salary range for this position is as listed on the requisition. Please note that the salary information listed is a general guideline only. Lockheed Martin considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/ training, key skills as well as market(work location) and business considerations when extending an offer.

Benefits offered

• Medical, Dental, Vision, Flexible work arrangements and schedules (e.g., 4x10), 401(k) match, Paid time off, Holidays, Parental Leave, EAP, Flexible Spending Accounts, Education Assistance, Life Insurance, Short-Term Disability, and Long-Term Disability.
• Annual short-term and/or long-term incentive compensation programs may be offered depending on the position. Payments under these annual programs are not guaranteed and can vary from year to year and are tied to a range of performance metrics.
• For (Washington state applicants only) Non-represented full-time employees: accrue at least 10 hours per month of Paid Time Off (PTO) to be used for incidental absences and other reasons; receive at least 90 hours for holidays. Represented full time employees accrue 6.67 hours of Vacation per month; accrue up to 52 hours of sick leave annually; receive at least 96 hours for holidays. PTO, Vacation, sick leave, and holiday hours are prorated based on start date during the calendar year.