Deputy CIO - Data, Analytics, AI

Primary Responsibilities

The Deputy CIO (DCIO) of data, analytics and artificial intelligence (DA&AI) provides executive leadership for leveraging data, analytics and AI to drive enterprise business value.  This includes exercising best practice product development and management approaches, instituting effective governance, to enable a culture of data-driven decision making and effective utilization of data assets and ecosystems across the enterprise.
This role includes the refinement, management and execution of the Laboratory data and analytics strategy and establishing an operating model for operational, technical and research data products and services. The DCIO is responsible for establishing and leading the operations of the DA&AI function; overseeing the continuous product development and management lifecycle, building trust and partnership with data domain owners and information licensing to ensure and manage high quality mission critical data; evolving technology capabilities, processes, and developing both talent and D&A culture. The DCIO for DA&AI reports to the CIO and works closely with the DCIO for Applications and the DCIO for Infrastructure, partners with business process owners, and is responsive to the Enterprise Capabilities Board for prioritization of projects.
This role is responsible for overseeing the strategy, architecture, development, operations, and support of Laboratory-wide data, analytics, AI applications and platforms, information research and archival preservation. It requires deep expertise in building and managing large-scale data ecosystems, along with strong collaboration skills to engage effectively with C-suite leaders, data owners, and key stakeholders.

The DCIO:

•    Refines, communicates and executes the DA&AI strategy, including vision, actions and outcomes for the R&D mission. Works in collaboration with the executive leadership, business and research domain leaders, and other relevant stakeholders.
•    Directs the execution of the full data, analytics, and AI portfolio—including data models, large language models, platforms, applications and systems, and infrastructure—ensuring that these platforms and applications are scalable, reliable, and seamlessly integrated to deliver maximum value to the organization.
•    Institutes an operating model including governance for DA&AI that is consistent with the capabilities and competencies required to execute the strategy. The operating model includes the ecosystem, architectures and delivery model.
•    Builds partnerships with executive leadership, business and research leaders to ensure that data is managed, curated, and, when required, preserved as a Lab critical asset, and is AI-ready. Establish and ensure appropriate tracking and measurement of the value derived from critical data assets. 
•    Communicates the tangible business value generated from DA&AI initiatives to stakeholders, executives, and the Lab community to institute a culture of data-driven decision-making and maximizes the value of data as a resource.
•    Supports the Laboratory research and operations as a single source for research and technical information resources and content, including the preservation and accessibility of Laboratory intellectual property via the Research Library and Laboratory Archives functions. 
•    Manage, preserve, make accessible Laboratory intellectual property and promote a culture of exploration, learning, discovery, networking, and collaboration.

In direct partnership and collaboration with data domain owners:

•    Ensures data quality, comprehensiveness and readiness to optimally support analytics used for decision making vital to the Lab mission and strategic direction. 
•    Oversees delivery of DA&AI products. Enables integrated product teams to deliver continuous, iterative improvements on key critical products using human-centric design and customer feedback loops.
•    Establishes and maintains trust in AI-ready data assets by instituting governance mechanisms for data including fostering data stewardship across business and research data domains. Includes other leaders that share responsibility for data, such as security, privacy, risk and compliance leaders.
•    Development of a data-driven culture, data literacy, related competencies, behaviors, and data and AI literacy across the enterprise. Leads these transformation efforts by developing talent and capability within the organization
•    Tracks the performance and adoption of the DA&AI products. Introduces metrics and OKRs (objectives and key results) to measure product success, customer impact, and data value realization.
•    Understands regulatory requirements, relevant data protection laws and regulations, and industry-specific standards. Ensures the organization's data practices are compliant, in collaboration with legal and compliance. 
•    In partnership with the CISO and the Chief Ethics and Compliance Officer, oversees the ethical and responsible use of data and algorithms used for artificial intelligence, analytics and automated decision making. Establishes guidelines and practices that prevent misuse of data and protect individual privacy, beyond regulatory and compliance requirements.

Required Skills and Qualifications

•    Experience: Minimum of 15 years in progressive IT or technical leadership roles as well as proven experience in a senior data, analytics, or AI leadership role, with a track record of successfully implementing business transformation and data-driven strategies in a complex organizational environment. 
•    Technical Proficiency: Strong understanding of data management, analytics, machine learning, and AI technologies, as well as experience with data visualization,  business intelligence tools and . Has direct experience overseeing product teams using standard agile methodologies such as Scrum or SAFe (scaled agile framework).
•    Leadership Skills: Exceptional leadership and interpersonal skills, with the ability to influence and engage stakeholders at all levels of the organization. Proven track record developing multi-disciplinary staff to improve collaboration and coordination across an organization as well as fostering the ability to strategize across boundaries. 
•    Communications Skills:  Strong verbal and written communications skills across all organizational levels to foster understanding and strong relationships that will advance this new strategy, improve access to operational plans to improve understanding and productivity and to minimize confusion and misunderstanding.
•    Educational Background: A bachelor’s or master’s degree in business, data science, computer science, statistics, or a related field.
•    Certifications: Desired, but not required, certifications in data science, AI, cloud platforms (AWS, Azure, Google Cloud), and project management (PMP, Agile)
•    Change Management Skills: Demonstrated experience assessing the impact of changes on impacted stakeholders, imploring effective training, support programs, and communications to promote successful transition and intended delivered value.
•    Business Acumen: Understanding of the broader business context and how data and AI initiatives align with organizational goals at MIT Lincoln Laboratory. Demonstrated ability to articulate the value of data and analytics in business terms, ensuring the focus on outcomes resonate with the Laboratory’s executive leadership and community
•    Analytical Mindset: Strong analytical and problem-solving skills, with the ability to translate complex data into actionable insights.