Mid-level Data Scientist (OBI Analytic Efficiency Enablement) - OBIQUA

Responsibilities

• Supports multiple DIA initiatives, including MARS, OMS, and OBI.
• Conducts data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis.
• Retrieves and analyzes information from various sources to build AI tools that automate certain processes.
• Designs, develops, and evaluates advanced algorithmic intelligence concepts, practices, and technologies for implementation into OBI via all-source analysis tradecraft, assessments, production, and dissemination.
• Collaborates with team members to develop and refine semantic data retrieval and reasoning across knowledge graphs through development and optimization of data queries via multiple protocols.
• Performs research studies to understand the process of augmenting or automating all-source analytic processes using various computer models.
• Provides incremental enhancements to tools, capabilities, processes, and methods.
• Reviews and evaluates OBI documentation submitted by advanced analytic (AA) owners to ensure compliance with tradecraft standards and adherence to best practices in AI system development and deployment.
• Assists analytic methodologists and AA owners in translating technical documentation into analytic tradecraft compliant language.
• Develops and tracks performance metrics to evaluate the effectiveness of systems in all source analysis.

Qualifications

• Minimum 8 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years.
• Bachelor’s degree.
• Prior experience with large data, spatial data, Multi-INT analytics, ML, and automated predictive analytics.
• Experience with major data science languages, such as R and Python.
• Skills in data visualization and use of graphical applications, including Microsoft Office (Power BI-) and Tableau.
• Experience with managing and merging of disparate data sources, preferably through R, Python, or SQL.
• Statistical analysis and data mining algorithms.
• Working knowledge of coding and scripting, information science, mathematics, machine learning, visual analytic modeling tools, and relevant Standard Operating Procedures (SOPs).
• Experience in distributed analytic environments, scaling algorithms to work on increasingly large and complex datasets that are larger than RAM.
• Knowledge of relevant theories, techniques, procedures and processes to investigate, prototype, and evaluate technologies to improve all-source intelligence analysis.

Benefits

• Comprehensive benefits package including company-paid employee and family dental insurance, employee health insurance, life insurance, and disability coverage.
• 401(k)-retirement plan with company matching.
• Paid holidays and personal time off.