Data Scientist

Job Description

COVID-19 continues to significantly impact our employees, families and communities. With employee health and safety as our top priority, and as a federal contractor, Lockheed Martin is taking action to address the increased risk and uncertainty COVID-19 variants pose in the workplace and ensuring we meet our commitments to national security.
To uphold safety for all employees, we will continue to request vaccination status for all Lockheed Martin employees including new hires. All current and newly hired employees are required to follow onsite safety measures based upon the COVID-19 Community Level at the specific work location.
Description:At Lockheed Martin, we are passionate about innovation and integrity. We believe that by applying the highest standards of business ethics and forward-thinking, everything is within our capacity – and yours as a Lockheed Martin employee. Lockheed Martin values your skills, training, education and background.
Do you want to be part of an environment that encourages and supports employees to think big, perform with quality and build incredible products? We provide the resources, encouragement, and focus - if you have the resourcefulness and courage to work hard, then we want to build a better tomorrow with you. Come and experience your future!
Data Analytics Innovations is a team of forward focused Data Scientists, Data Engineers, and Software Engineers that rapidly develop full stack analytics and machine learning software to support our customer’s mission. Our teams are fully integrated and empowered to work with our external and internal customers to create solutions at the speed of relevance. We focus on providing extensible tools that can be shared outside our organization but also collaborate with our customers to develop custom analytics and machine learning applications. Our teams collaborate across time zones using modern software and algorithm development tools to support engineering, production, maintenance, and business needs.
Primary Responsibilities:
• 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:
• Bachelor’s degree from an accredited college in a related discipline, or equivalent experience/combined education, with 5 years of professional experience; or 3 years of professional experience with a related Master’s degree. Considered career, or journey, level.
• Experience with Tensorflow or PyTorch, SciKit Learn, Pandas, and Numpy/SciPy
• Experience building AI/ML models in python
• Experience developing containerized model deployments
Desired Skills:
• Previous experience in machine learning as applied to mechanical and electrical engineering problems
• Experience working with model explainability (e.g. LIME, SHAP)
• Experience in model sustainment and continuous evaluation
• Additional experience in the following areas is desired:
git, SQL, Data Virtualization, MLOps, KServe, LakeFS