Role: Research Delivery Manager

Location: Whippany, NJ or New York City, NY (Hybrid – 3 days/week onsite)
Duration: 12 Months
Function: Digital Research Technology / Technology Delivery

Position Overview:

We are seeking an experienced Research Delivery Manager to lead the execution of strategic technology, data, analytics, and AI initiatives supporting the Research organization. This is a highly visible delivery leadership role requiring a strong Program/Project Manager with exceptional communication, organizational, and executive stakeholder management skills.

The successful candidate will be responsible for translating business objectives into actionable delivery plans, coordinating execution across multiple technology and business teams, managing dependencies and risks, and ensuring initiatives remain on track through implementation and transition into ongoing operations.

This role will work closely with senior business leaders, technology leadership, engineering, data, architecture, operations, risk, compliance, information security, and other control functions. The individual should be comfortable operating in a complex, matrixed environment and engaging with CxO-level stakeholders.

An AI-first mindset is highly desirable. Candidates with experience delivering or managing initiatives involving Agentic AI, Generative AI, Claude, OpenAI, AI-enabled analytics, or modern AI platforms will be strongly preferred.

Key Responsibilities:

Program & Delivery Leadership

• Lead end-to-end delivery of complex technology, data, analytics, and AI initiatives from initial planning through implementation, stabilization, and transition to BAU.

• Translate strategic objectives into structured execution plans, roadmaps, milestones, workstreams, and measurable outcomes.

• Develop and maintain detailed integrated project plans covering timelines, milestones, resources, dependencies, deliverables, and critical paths.

• Drive execution across multiple concurrent workstreams while ensuring alignment with business priorities.

• Monitor delivery progress and proactively identify risks, issues, blockers, and schedule impacts.

• Establish clear ownership and accountability across participating teams.

• Escalate critical issues and decisions to the appropriate leadership forums to maintain delivery momentum.

• Coordinate release planning, implementation activities, readiness assessments, production deployment, and post-production stabilization.

• Ensure projects are delivered within agreed scope, timelines, quality expectations, and governance requirements.

Cross-Functional Program Coordination

• Serve as the central delivery point across Research, Technology, Data Engineering, Architecture, Infrastructure, Operations, Information Security, Legal, Compliance, Risk, and other stakeholder groups.

• Coordinate teams with different priorities and operating models to ensure dependencies and commitments are clearly understood.

• Facilitate cross-functional working sessions to resolve issues, clarify ownership, and maintain progress.

• Identify organizational and technical dependencies early and develop mitigation strategies.

• Remove execution barriers by driving collaboration and timely decision-making across teams.

• Lead project meetings, working groups, steering committees, governance sessions, and executive reviews.

Executive & CxO Stakeholder Management

• Build and maintain trusted relationships with senior business and technology leaders, including CxO-level stakeholders.

• Act as the primary interface between business leadership and delivery organizations.

• Prepare concise and executive-ready status updates, steering committee materials, management presentations, dashboards, and decision papers.

• Clearly communicate program health, milestones, risks, dependencies, financial/resource considerations, and key decisions.

• Tailor communication appropriately for executives, technical teams, business users, and control functions.

• Facilitate difficult conversations and drive alignment where priorities or expectations differ.

• Ensure leadership has timely visibility into issues requiring decisions or intervention.

Governance, Risk & Controls

• Establish and maintain appropriate delivery governance throughout the program lifecycle.

• Coordinate required reviews and approvals with Risk, Compliance, Legal, Information Security, Architecture, and other control functions.

• Maintain program-level oversight of risks, assumptions, issues, dependencies, decisions, and mitigation actions.

• Ensure required documentation, approvals, controls, and evidence are completed and traceable.

• Support audit and regulatory requirements and ensure delivery activities remain aligned with organizational policies and standards.

• Drive appropriate governance for data, analytics, and AI initiatives, including required control and risk-management processes.

Planning, Metrics & Dependency Management

• Develop comprehensive delivery plans covering multiple teams, initiatives, and technology components.

• Coordinate resource and capacity planning with functional leaders and delivery teams.

• Establish delivery KPIs, milestones, reporting mechanisms, and health indicators.

• Track schedule, scope, dependencies, risks, and execution performance.

• Identify cross-program impacts and proactively address dependencies that could affect delivery.

• Provide regular reporting to senior leadership on overall program status and emerging concerns.

Operational Readiness & BAU Transition

• Lead planning activities required to ensure solutions are operationally ready before production deployment.

• Partner with engineering, platform, infrastructure, operations, and support teams to define sustainable ownership and operating models.

• Coordinate readiness activities covering monitoring, production support, incident management, service management, maintenance, and escalation processes.

• Ensure runbooks, support documentation, SLAs, training materials, and operational procedures are completed before go-live.

• Coordinate knowledge transfer from project teams into production support and business-as-usual organizations.

• Ensure newly implemented capabilities transition smoothly into sustainable operating models.

Change Management & Adoption

• Support organizational change and adoption activities associated with new technology, data, analytics, and AI capabilities.

• Develop stakeholder engagement and communication plans.

• Coordinate user communications, training, enablement, and knowledge-transfer activities.

• Gather feedback from Research users, business stakeholders, technology teams, and support organizations.

• Incorporate feedback into continuous improvement initiatives.

• Ensure impacted teams understand changes, responsibilities, processes, and support models.

AI & Emerging Technology Focus:

• Bring an AI-first approach to program delivery and identify opportunities where AI can improve Research workflows, productivity, data analysis, and decision-support capabilities.

• Experience coordinating AI or Generative AI initiatives across business and technology teams is highly desirable.

• Familiarity with Agentic AI, AI agents, LLM-based solutions, Claude, OpenAI, Generative AI platforms, and AI-enabled analytics is preferred.

• Understand the delivery considerations associated with enterprise AI, including governance, security, data privacy, model risk, controls, operationalization, and adoption.

• Partner with technical teams to translate AI concepts and use cases into structured delivery plans and executable programs.

• Stay current with emerging AI capabilities and help stakeholders understand practical implementation considerations.

Required Qualifications:

Delivery & Program Management:

• 7+ years of experience managing complex technology, data, digital transformation, or enterprise delivery programs.

• Demonstrated experience leading large-scale initiatives involving multiple workstreams and stakeholder groups.

• Proven ability to take initiatives from planning through implementation, stabilization, and operational handoff.

• Strong command of project planning, execution management, milestone tracking, dependency management, risk management, and resource coordination.

• Experience managing multiple initiatives simultaneously in a fast-moving enterprise environment.

• Practical experience working with Agile, Waterfall, and hybrid delivery methodologies.

Leadership & Communication:

• Exceptional written and verbal communication skills.

• Demonstrated ability to communicate effectively with senior executives and CxO-level stakeholders.

• Strong executive presence with the ability to simplify complex technology or delivery topics for business leadership.

• Proven ability to influence teams without direct authority.

• Strong facilitation, negotiation, presentation, and decision-making skills.

• Ability to build relationships and drive alignment across complex, matrixed organizations.

Technology & Data:

• Strong understanding of enterprise technology delivery, data platforms, analytics environments, and software development lifecycles.

• Working knowledge of data engineering concepts, cloud technologies, APIs, data integration, and modern enterprise data architectures.

• Ability to effectively partner with Data Engineering, Architecture, Infrastructure, Security, and Engineering teams.

• Understanding of modern analytics, AI, and data platform technologies.

• Experience managing technology initiatives where business outcomes depend on multiple interconnected platforms or teams.

Governance & Controls

• Experience working within highly governed or regulated enterprise environments.

• Understanding of risk management, compliance, information security, audit, and technology governance processes.

• Experience coordinating reviews, approvals, control activities, operational readiness, and supporting documentation.

• Strong understanding of delivery governance and the ability to establish appropriate controls without slowing execution.

Execution & Problem Solving

• Strong analytical and problem-solving capabilities.

• Ability to work effectively with ambiguity and rapidly changing priorities.

• Highly organized with strong attention to detail.

• Ability to manage competing priorities while maintaining focus on key delivery outcomes.

• Demonstrated ability to identify blockers, drive resolution, and keep complex initiatives moving forward.

• Comfortable working across a large, matrixed organization with multiple decision-makers and competing priorities.

Preferred Qualifications

• Experience within Financial Services, Banking, Capital Markets, Investment Research, Asset Management, or a similar regulated environment.

• Experience supporting Research organizations or investment research platforms across multiple asset classes.

• Background delivering enterprise data, analytics, AI, or digital transformation programs.

• Experience working with senior leadership and executive governance forums.

• Experience delivering Generative AI, Agentic AI, AI automation, LLM, Claude, OpenAI, or AI-enabled analytics initiatives.

• Familiarity with AI governance, model risk, data privacy, security, and enterprise AI controls.

• Relevant professional certifications such as PMP, PgMP, PRINCE2, PMI-ACP, SAFe, Scrum/Agile certifications, or equivalent program/project management credentials are preferred.

• Certifications or formal training related to AI, Generative AI, Cloud, Data, or Digital Transformation are also desirable.

Ideal Candidate Profile:

The ideal candidate is a senior delivery-focused Program/Project Manager rather than a purely technical specialist. They should be highly organized, proactive, and comfortable owning execution across multiple teams.

The individual will be expected to:

• Turn strategy into clear and actionable delivery plans.

• Keep complex initiatives on schedule and continuously follow up on commitments.

• Establish accountability across teams and manage dependencies proactively.

• Communicate confidently with business leaders, technology leadership, and CxO-level stakeholders.

• Navigate organizational complexity and resolve issues without waiting for direction.

• Bring structure to ambiguous initiatives.

• Balance delivery speed with governance, risk, and control requirements.

• Understand enough about data, technology, and AI to effectively coordinate technical teams.

• Demonstrate an AI-first mindset and familiarity with modern AI technologies and delivery models.

• Maintain strong focus on execution, communication, stakeholder alignment, and measurable outcomes.