Program Manager, Data Science Core – GenAI Studio

The College Board

. Establish operating rhythms for planning, status, decision-making, risk review, and retrospectives .

Posted 11/1/2026full-timeRemote • United StatesSeniorLead💰 $120 - $170 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading complex programs across data science, analytics, and software environments, with a strong focus on stakeholder alignment, risk management, and clear communication. Proficient in translating ambiguous goals into actionable plans while ensuring compliance with data quality and privacy standards.

Highest-signal resume keywords

Program ManagementData Science LifecycleCross-Functional CollaborationRisk ManagementStakeholder Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceAnalyticsMachine LearningProgram DeliveryPortfolio ManagementRisk ReviewDecision-MakingData QualityComplianceAgile Practices

Soft Skills

Clear CommunicationCuriosityAccountabilityCollaborative ApproachLearner's Mindset

Tools & Technologies

Collaboration ToolsProgram Management ToolsAgile MethodologiesIterative PracticesStage-Gated Practices

Industry Keywords

Data GovernancePrivacyResponsible AITechnical EnvironmentCross-Team Dependencies

About the role

Key responsibilities & impact

Establish operating rhythms for planning, status, decision-making, risk review, and retrospectives
Drive alignment across data science, engineering, and product stakeholders
Identify delivery, data, model, compliance, and resourcing risks; drive mitigation and escalation
Track program health and outcomes using meaningful measures
Maintain roadmaps, dependency maps, decision logs, risk registers, and executive-ready updates
Coordinate work across data science, research, product, engineering, analytics, privacy, legal, security, and business teams
Build executable plans from ambiguous goals and align scope, responsibilities, milestones, dependencies, and acceptance criteria
Facilitate decisions and resolve blockers
Manage handoffs from research and prototyping through production delivery, adoption, and operational ownership
Translate Data Science strategy and business priorities into a portfolio of programs, workstreams, milestones, and measurable outcomes
Own integrated roadmaps and planning processes from experimentation through deployment
Lead intake and prioritization with Data Science leaders
Establish readiness criteria covering data access, legal and privacy review, business ownership, and success measures
Define program success measures, ownership, decision rights, and escalation paths
Build stakeholder alignment and adoption through clear communication and feedback loops
Prepare recommendations and decision materials for leaders
Partner with Data Science leadership on capacity planning, team growth, role clarity, and sustainable delivery practices
Improve prioritization, documentation, reuse, knowledge sharing, and continuous improvement across programs
Support an inclusive and accountable team environment

Requirements

What you’ll need

8 or more years of experience leading complex programs or portfolios in data science, analytics, machine learning, software, research, or another technical environment
Record of delivering cross-functional programs from initial problem framing through implementation, adoption, and measurement
Familiarity with, or ability to quickly build working knowledge of, the data science lifecycle, including data readiness, experimentation, model development and validation, deployment, monitoring, and iteration
Ability to translate ambiguous goals into clear plans, milestones, ownership, dependencies, risks, and decisions
Sound portfolio and prioritization practices
Ability to identify and manage cross-team dependencies and drive resolution across teams not directly managed
Clear communication with executives, technical teams, researchers, and business partners; ability to explain technical tradeoffs, uncertainty, and data or model limitations in plain language
Familiarity with data quality, privacy, governance, security, and responsible AI considerations
Effective use of program management and collaboration tools; adaptability to agile, iterative, or stage-gated practices
Strong judgment, curiosity, accountability, inclusive collaboration, and continuous learning
Passion for expanding educational and career opportunities and mission-driven work
Curiosity and enthusiasm for emerging technologies, willingness to experiment with and adopt AI-driven solutions, and comfort learning new digital tools independently
Clear and concise written and verbal communication skills
Learner's mindset and commitment to growth
Drive for impact and excellence
Collaborative and empathetic approach
Ability to travel 3 to 5 times per year to New York City or Reston, Virginia
Authorized to work in the United States

Benefits

Comp & perks

Meaningful career
Supportive team
Comprehensive package designed to help you thrive
Fair and competitive compensation
Location-adjusted salaries for fairness
Transparent conversations about compensation and benefits throughout the hiring process