LMI is seeking a Junior Data Scientist to support a Special Operations customer in Coronado, CA.

*This position is on-site at Coronado, California*

• Work with analysts to interpret analytic results and refine analysis as needed. Collaborate with Intelligence Analysts to understand needs and devise possible solutions.
• Apply machine learning techniques to identify and transform data features, find hidden patterns and trends, build and optimize classifiers, create automated anomaly detection systems, and automate steps of the intelligence process.
• Communicate results and ideas to key decision makers, analysts and other stakeholders. Contractor shall advise on the interpretation and use of data intelligence products, quality assessments and applications.

• Bachelors dergee in Data Science, Statistics, Applied Math, or related STEM field is required. Master’s degree is preferred
• 1+ years applying statistics, machine learning and analytic approaches to answer key intelligence questions, producing results and re-usable products that provide value to Intelligence Analysts.
• Ability to obtain an interim Top Secret clearance in a timely manner is required. TS/SCI clearance is preferred.
• Must be proficient with at least one programming language (Java, C++, Python, R, etc.)
• Proficient in Agile Development and Git Operations
• Demonstrated experience applying data science methods to real-world data problems
• Outstanding communication skills, written and verbal
• Highly organized and able to manage multiple projects simultaneously
• Team-player mentality with a positive attitude
• Keen attention to detail and solid analytical skills
• Able to articulate complex, abstract concepts concisely and effectively

• Demonstrated proficiency with Python and SQL to manipulate data and draw insights from large data sets.
• Demonstrated proficiency in a variety of supervised and unsupervised machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Demonstrated proficiency in advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Demonstrated proficiency with common data science libraries.
• Demonstrated proficiency visualizing/presenting data for stakeholders.
• Capability to recognize when Data Science can add value to an intelligence problem, and when it cannot.