Leidos is hiring a Data Scientist in McLean, Virginia, to support a team of researchers in deployment of the latest automated vehicle technology. The Data Scientist will be a key part of the Leidos team supporting the Federal Highway Administration's (FHWA's) cutting-edge research at Turner Fairbank Highway Research Center (TFHRC). The role will be part of a larger research team that develops new connected and automated vehicle technologies for FHWA.
This role will support the Saxton Transportation Operations Laboratory, a state-of-the-art facility for conducting connected and automated vehicle research. The laboratory enables FHWA to validate and refine new transportation services and technologies. The position will assist in the processing, cleansing and verifying the integrity of data used for analysis throughout intelligent transportation. This includes efficient application of machine learning techniques and algorithms. The successful candidate has practical experiences with applied statistics skills, such as distributions, statistical testing and regression. Technical writing experience and a knowledge of the USDOT, transportation industry, connected and automated vehicles (CAV), Intelligent Transportation Systems (ITS), and emerging technologies are preferred.
• Analyzes data to identify and compare norms, trends, and patterns.
• Validates data analysis results and analytically identifies anomalies.
• Conducts self-directed research to uncover problems and provides data analysis support to the team in support of their projects.
• Responds in a timely and complete manner to data requests from internal and external customers.
• Writes technical documents that describe handling and functionality of various data architectures and solutions.
• Software development, data architecture development, database operation and administration.
• Develop, operate and administer data warehouse(s).
• Support logistics for working with FHWA editors and FHWA Public Affairs as needed on the development and publication of communication materials and media.
• Build and maintain trust with key FHWA stakeholders to facilitate communication on R&D priorities.
Required Education, Skills, and Experience:
• Master's Degree in a quantitative discipline and 2+ years of analytics experience or Bachelor's Degree in a quantitative discipline and 4+ years of analytics experience to include:
o 2+ years hands on experience in applied machine learning
o 2+ years using data mining methods, such as clustering and anomaly detection, to understand data patterns and select appropriate predictive techniques.
• Ability to obtain and maintain a Public Trust clearance.
• Processing, cleansing, and verifying the integrity of data used for analysis.
• Excellent understanding of machine learning techniques and algorithms.
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Good scripting and programming skills.
• Data-oriented personality.
• Proficiency in using query languages such as SQL, Hive, Pig.
• Experience with NoSQL databases, such as MongoDB, Cassandra, HBase.
• Fluent with Microsoft Office tools/programs, especially Word, PowerPoint, and Excel.
• Excellent verbal, written, and communication skills in English.
• Capable of transforming complicated subject matter and diverse source material into coherent, engaging, and accurate communications for a variety of audiences.
• Ability to work independently and with small teams.
• Strong work ethic and entrepreneurial spirit.
• Ability to thrive in highly flexible, rapidly changing, ambiguous work environment.
• Strong interpersonal skills, maturity, and tact.
• Ability to work under pressure and meet tight deadlines across multiple projects simultaneously, prioritizing demands on a daily, weekly, and monthly basis.
Desired Skills and Experience:
• Strong project management skills.
• Demonstrated initiative and resourcefulness.
• Ability to learn substance of research quickly and the intellectual curiosity and dedication to master vast and complex subjects.
• Skilled at cultivating and managing relationships.
• Proven and measureable track record in business development.
• Worked with data visualization tools such as: ggplot, d3.js and Matplottlib, and Tableau
• Demonstrated knowledge in Machine Learning and AI with techniques such as: neural networks, recurrent and convolutional networks, and decision trees.
External Referral Bonus:
Potential for Telework:
Clearance Level Required:
Yes, 10% of the time
Scheduled Weekly Hours: