Data Scientist (All Levels)

$166,800 - $260,625/Yr

Noblis - McLean, VA

Part-time,Full-time - Entry Level

McLean, VA

Professional, Scientific, and Technical Services

About the position

Noblis is seeking a technical thinker and doer to work as a Data Scientist within a highly dynamic and impactful operating environment located in McLean, VA. The Data Scientist will play a crucial role in acquiring data from primary or secondary sources and maintaining databases and data systems. This position involves structuring large data sets to extract usable information using advanced Information Technology techniques. The Data Scientist will design, develop, implement, and maintain databases, data collection systems, and data analytics strategies that optimize statistical efficiency and quality. In this role, the Data Scientist will troubleshoot data issues and provide quality assurance for imported data, collaborating with quality assurance analysts as necessary. They will identify, analyze, and interpret trends or patterns in complex data sets, making predictions based on these data trends. The Data Scientist will also assess, test, and implement new or upgraded software, assisting with strategic decisions regarding new systems. Establishing key performance indicators to measure the effectiveness of business decisions will be a critical responsibility, along with monitoring performance and quality control plans to identify areas for improvement. Collaboration is key in this role, as the Data Scientist will work closely with programmers, engineers, and organizational leaders to identify opportunities for process improvements, recommend system modifications, and develop policies for data governance. They will assist in establishing and prioritizing business and information needs, conduct data lifecycle analysis, and define new data collection and analysis processes. Additionally, the Data Scientist will create documentation for stakeholders to effectively communicate trends, patterns, and predictions using relevant data. Managing and designing data environments, including data sources, security, and metadata, will also be part of their responsibilities, along with providing technical expertise on data storage structures, data mining, and data cleansing. The use of graphs, infographics, and other methods to visualize data will be essential in this role.

Responsibilities

• Acquire data from primary or secondary data sources and maintain databases/data systems.
• Structure large data sets to find usable information using Information Technology.
• Design, develop, implement and maintain databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality.
• Troubleshoot data and provide quality assurance of imported data, working with quality assurance analysts if necessary.
• Identify, analyze, and interpret trends or patterns in complex data sets; make predictions based on data trends.
• Assess, test, and implement new or upgraded software and assist with strategic decisions on new systems.
• Help establish key performance indicators to measure the effectiveness of business decisions.
• Monitor performance and quality control plans to identify improvements; support initiatives for data integrity and normalization.
• Collaborate with programmers, engineers, and organizational leaders to identify opportunities for process improvements, recommend system modifications, and develop policies for data governance.
• Assist with establishing and prioritizing business and information needs.
• Conduct data lifecycle analysis to include requirements, activities and design; define new data collection and analysis processes.
• Create appropriate documentation for stakeholders to effectively communicate trends, patterns, and predictions using relevant data.
• Manage and design the data environments, including data sources, security, and metadata; evaluate changes and updates to data systems; provide technical expertise on data storage structures, data mining, and data cleansing.
• Use graphs, infographics and other methods to visualize data.

Requirements

• Active TS/SCI with Polygraph.
• Experience using ML and data science packages such as PyTorch, TensorFlow, or scikit-learn and developing and training machine learning models.
• Experience leveraging various computing resources such as GPU clusters and cloud-based compute servers.
• Experience with databases such as PostgreSQL, MySQL, Oracle, MongoDB.
• Programming knowledge in some of the following languages: Python, SQL, Java.
• Experience working with Docker, Kubernetes.
• Proficiency with git and pull request workflows.
• Experience performing extract, transform, load (ETL) development for data pipelines.
• Ability to perform API service development.
• Demonstrated experience working with IC Agencies.
• Knowledge of IC systems, processes, data, and policies.
• Knowledge and application of agile techniques and methodologies.
• Experience mentoring or training (through formal or informal means) members of the team.

Nice-to-haves

• Strong communication skills, written and verbal.

Benefits

• Health insurance coverage.
• Life insurance coverage.
• Disability insurance coverage.
• Financial and retirement benefits.
• Paid leave.
• Professional development opportunities.
• Tuition assistance programs.
• Work-life balance programs.