Cleared Data Analyst

Guidehouse•Washington, DC

1d•$113,000 - $188,000

About The Position

Guidehouse’s Defense & Security AI & Data team helps clients maximize the value of data and automate business processes through data analytics and data science, including data querying and wrangling, engineering, visualization, dashboarding, business intelligence, predictive analytics, machine learning, artificial intelligence, and robotic process automation. The team supports information strategy, mission-critical insights and data-driven decision-making, cost and complexity reduction, trust, and operational effectiveness. This consultant works collaboratively on client services and may also support business development, internal firm initiatives, and professional development. The role focuses on cybersecurity metrics and the use of available cybersecurity and IT asset data, helping convey underlying risk areas and progress in mitigating those risks. The position supports cybersecurity dashboard and scorecard operations for agency leadership, evaluates and integrates agency cybersecurity data sources, and aligns risk and performance measures with the National Institute of Standards and Technology Cybersecurity Framework. The role requires an active and maintained Secret clearance and the ability to support on-site and hybrid projects in the DC metro area.

Requirements

Active and maintained Secret federal or DoD security clearance.
Bachelor’s degree.
At least 3 years of relevant professional experience, or 2 years of relevant professional experience with a master’s degree.
High proficiency in Python.
Expertise in Tableau dashboard development.
Experience manipulating large data sets and using them to identify trends and inform strategic business decisions.
Ability to clean, aggregate, and organize data from multiple sources and transfer it to data warehouses.
Ability to define data requirements and ensure the storage, availability, and coherence of electronically stored information.
Competency in data mining, including structuring raw data to formulate or recognize patterns and generate useful insights.
Ability to support on-site and hybrid projects in the DC metro area.

Nice To Haves

Familiarity with externally reported data sources, such as agency-reported data provided under Chief Information Officer Federal Information Security Modernization Act Metrics guidance.
Proficiency in Power BI.
Knowledge of additional coding languages such as R and SQL.
Competencies in IT risk and/or cybersecurity domains.
Quality control experience, including debugging and quality assurance of new features and enhancements.
Ability to facilitate meetings and present topics to diverse groups of functional and technical staff.
Experience developing new processes and redesigning existing processes to meet new or evolving business requirements.
Excellent verbal and written communication skills.

Responsibilities

Collaborate with cross-functional teams as a data science, data analytics, or business intelligence professional.
Support client services, business development, internal firm initiatives, and ongoing professional development.
Drive cybersecurity dashboard and scorecard operations for agency leadership.
Recommend new cybersecurity metrics, their weighting, and alignment with existing metrics and displays.
Evaluate and integrate agency cybersecurity data sources for suitability, reliability, automated reporting, and scoring.
Align risk and performance measures to the Identify, Protect, Detect, Respond, and Recover functions of the National Institute of Standards and Technology Cybersecurity Framework.
Design data modeling processes, create algorithms and predictive models, and perform custom analysis.
Lead data-driven analytic activities to identify indicators of compliance and effectiveness that are critical to mission and business success.
Manipulate large data sets to identify trends and produce conclusions that inform strategic business decisions.
Clean, aggregate, and organize data from multiple sources and transfer it to data warehouses.
Define data requirements and ensure electronically stored information is stored, available, and coherent to meet organizational needs.
Mine and structure raw data to identify patterns and generate information and insights that help the organization manage risks.