Vice President, Enterprise Strategy & Intelligence

DecisionPoint | Cortek•Reston, VA

2d•Hybrid

About The Position

DecisionPoint Corporation is seeking a Vice President, Enterprise Strategy & Intelligence, a cross-functional leader responsible for turning strategic ideas, emerging technologies, company data, and operational challenges into executable solutions that accelerate DecisionPoint’s growth and improve how the company operates. The Vice President serves as a bridge between Growth and Capture, Operations, Technology, and Executive Leadership. This role is both strategic and hands-on, expected to identify opportunities, develop strategies, prototype solutions, build frameworks, mobilize stakeholders, and drive ideas through implementation. This is a hybrid position, with in-person meetings at DecisionPoint offices in Reston, Virginia as required. Upon future contract award and assignment to a program, travel will be required based on program and customer needs.

Requirements

Bachelor’s degree in Business, Technology, Data/Analytics, Information Systems, Engineering, or a related field; equivalent experience considered.
10+ years of progressive experience spanning strategy, technology, solution development, consulting, operations, or enterprise transformation.
Demonstrated experience translating complex business or customer problems into actionable strategies and solutions.
Experience leading cross-functional, enterprise-level initiatives from concept through implementation.
Strong understanding of AI, data analytics, automation, and emerging technologies, with demonstrated ability to identify and operationalize practical use cases.
Experience using organizational data to develop insights, metrics, dashboards, decision-support capabilities, or business intelligence.
Experience developing solutions in a pre-award, consulting, federal contracting, or complex customer environment.
Ability to rapidly assess unfamiliar problems, synthesize complex information, and develop clear recommendations for senior leadership.
Demonstrated ability to influence and execute across organizational boundaries without direct authority.
Exceptional executive communication, facilitation, presentation, and storytelling skills.

Nice To Haves

IT / AI Certifications preferred

Responsibilities

Serve as the company's Data Officer, establishing the strategy and mechanisms necessary to turn fragmented corporate data into trusted, actionable enterprise intelligence.
Develop and execute DecisionPoint's enterprise data strategy.
Identify critical company data across Growth, Finance, HR, Recruiting, Operations, Contracts, Delivery, and other business functions.
Establish a common understanding of what data exists, where it resides, who owns it, how it connects, and how it can be used.
Define data governance, stewardship, quality, accessibility, security, and lifecycle practices appropriate to the organization.
Develop enterprise data models, dashboards, metrics, and analytical capabilities that provide leadership with improved visibility into company performance.
Identify opportunities to integrate data across corporate systems and reduce manual reconciliation and disconnected reporting.
Establish trusted metrics and authoritative data sources for key business decisions.
Partner with functional leaders to convert business questions into measurable data products, analytics, and decision-support capabilities.
Lead the practical application of AI as a business and growth accelerator, focusing on measurable problems rather than technology for technology's sake.
Develop and maintain a prioritized portfolio of enterprise AI use cases.
Identify high-value opportunities for AI, intelligent automation, analytics, and agentic workflows across Growth and corporate operations.
Rapidly prototype and evaluate emerging AI technologies against real DecisionPoint business problems.
Develop AI-enabled workflows that improve research, solution development, knowledge management, analysis, reporting, decision support, and repetitive business processes.
Establish repeatable methods for moving AI concepts from idea → prototype → pilot → production → measurement.
Evaluate emerging AI platforms, models, vendors, and capabilities and recommend where DecisionPoint should invest, partner, build, or avoid.
Establish responsible AI practices addressing security, data protection, human oversight, accuracy, governance, and acceptable use.
Build organizational AI literacy and help functional teams redesign processes around new capabilities rather than simply layering AI onto existing workflows.
Identify opportunities where internal AI capabilities can become customer-facing differentiators, accelerators, or offerings.
Serve as an enterprise problem solver for high-priority initiatives that cross traditional organizational boundaries.
Lead special projects sponsored by executive leadership from problem definition through implementation.
Diagnose ambiguous or complex business challenges and develop structured, actionable solutions.
Conduct research, analysis, benchmarking, technology assessments, and business cases.
Build cross-functional teams around strategic initiatives and drive execution across organizational boundaries.
Develop pilots and minimum viable solutions to validate concepts before larger investments are made.
Establish objectives, measures, milestones, risks, dependencies, and executive reporting for strategic initiatives.
Step into emerging corporate priorities where dedicated leadership or structured problem solving is required.
Partner with Growth, Capture, Operations, technical SMEs, partners, and executive leadership to transform capture strategies into credible, differentiated, and executable solutions.
Support development and operationalization of technical and management solutions for strategic pursuits.
Develop solution blueprints, CONOPS, frameworks, processes, transition approaches, technical strategies, and implementation roadmaps.
Connect DecisionPoint capabilities across AI/ML, cloud, cybersecurity, data engineering, digital engineering, and enterprise IT into cohesive customer solutions.
Ensure proposed solutions are operationally realistic, technically defensible, measurable, and executable by delivery teams.
Create reusable solution assets, accelerators, methodologies, and intellectual property that can be leveraged across multiple pursuits.
Bring greater structure, repeatability, automation, and data-driven decision-making to the pre-award solutioning process.