International Monetary Fund
Section Chief, Data Science (Econometrics and Big Data)-ITDDPDS
- 勤務地
- 🇺🇸 United States
- 国 / 地域
- United States
- 地域
- Americas
- 国連システム
- Specialized Agency
この役割について
The IMF's Information Technology Department seeks a Data Science Section Chief to lead strategic planning and delivery of data science, econometric, and big data solutions. This role involves overseeing advanced econometric modeling, computational economics, analytics, and machine learning to meet business, policy, and research needs. The Section Chief manages multiple complex projects, leads a high-performing team, and collaborates with economists, financial specialists, and cross-functional IT teams. Key responsibilities include defining strategic roadmaps, managing data pipelines and analytical platforms, translating business needs into technical solutions, and ensuring scalable, secure, and efficient systems. The position requires strong leadership, technical expertise, and the ability to work across organizational units to deliver shared objectives.
必須条件
- 8+ years relevant professional experience
- Advanced university degree in Computational Economics or Finance, Computer Science, Statistics, or related field
- Strong background in econometric, economic, financial, and/or statistical modeling
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要件の概要
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- Minimum 8 years of relevant professional experience; or a bachelor's degree in Computational Economics or Finance, Computer Science, Statistics, or related field plus a minimum of 14 years of relevant professional experience.
- 必要学位
- Advanced university degree in Computational Economics or Finance, Computer Science, Statistics, or related field required; or a bachelor's degree in Computational Economics or Finance, Computer Science, Statistics, or related field with 14 years of relevant professional experience.
Work for the IMF. Work for the World.
Job Summary
The Information Technology Department (ITD) Data Platform Division is seeking to hire a Data Science Section Chief. Reporting to the Deputy Division Chief, the Data Science Section Chief oversees planning and delivery of data science, econometric, and big data solutions. This role leads efforts in econometric modeling, computational economics, analytics, and machine learning to ensure platforms meet business, policy, and research needs.
The role combines strategic leadership, people management, and deep technical oversight.
The Section Chief partners closely with economists, financial sector specialists, business stakeholders, cross-functional IT teams, and external vendors to deliver scalable, reliable, and high-quality analytical systems. The position is accountable for multiple complex projects and for fostering a collaborative, innovative, and results oriented team culture.
Key Duties and Responsibilities
Define and lead the strategic vision, roadmap, and delivery of data science, econometric modeling, big data analytics, machine learning, and high-performance computing capabilities.
Provide strong intellectual, technical, and people leadership across all data science and modeling activities.
Oversee the design, development, deployment, and operational support of advanced econometric, statistical, and machine learning models and platforms.
Ensure scalable, secure, and efficient data pipelines and analytical solutions for structured and unstructured data.
Serve as the primary point of contact and trusted advisor to business stakeholders, translating policy and business needs into analytical solutions.
Manage multiple complex projects and platforms, ensuring timely, high-quality delivery within agreed scope, cost, and timelines.
Build, lead, and develop a cohesive, diverse, and high performing team through coaching and performance management.
Define work plan and objectives for the team, communicates work assignments, and provides advice, guidance, encouragement, and constructive feedback.
Manage section resources, including staffing, budgets, and technology assets, and recommend reallocations as needed.
Promote collaboration and teamwork within the section and across organizational units and works closely with business partners and stakeholders to deliver shared objectives.
Stay current with advances in data science, econometrics, machine learning, and computational technologies and guide their adoption to enhance business value.
Minimum Qualifications
Educational development, typically acquired through the completion of an advanced university degree in Computational Economics or Finance, Computer Science, Statistics, or related field, plus a minimum of 8 years of relevant professional experience; or a bachelor's degree in Computational Economics or Finance, Computer Science, Statistics, or related field plus a minimum of 14 years of relevant professional experience is required.
Experience
Strong background in econometric, economic, financial, and/or statistical modeling.
Demonstrated expertise in data science, big data analytics, and/or machine learning solutions.
Strong foundation in computational science or scientific computing, including distributed and parallel computing architectures.
Experience designing and managing largescale analytical platforms, data pipelines, and modeling tools across cloud and on-premises environments.
Proven experience managing teams, complex projects, and stakeholder relationships in a fast-paced environment.
Skills
Ability to stay current with academic research in computational economics, quantitative finance, applied mathematics, and statistics.
Ability to quickly understand and apply new technologies to achieve business goals.
Strong analytical, problem solving, and decision-making skills in complex and ambiguous environments.
Proven ability to influence senior stakeholders across multiple business units.
Strong facilitation, conflict management, and interpersonal skills that foster trust and effective working relationships.
Demonstrated team leadership, including building high performing teams and fostering professional development.
Strong verbal and written communication skills with technical and non‑technical audiences.
Client service orientation, flexibility, and ability to provide strategic direction aligned with organizational objectives.
A regular staff member who is selected to fill the vacancy will maintain their open-ended status. If the selected candidate is a contractual employee, they will be offered a Term staff appointment. Staff members already on a term appointment will continue their current term but may receive an extension provided that their current term appointment has not already been extended.
The position requires Review Committee /Senior Review Committee Approval.
Department:
ITDDPDS Information Technology Department Data Platform Division Data Science SectionHiring For:
A13, A14The IMF is guided by the principle that the employment, classification, promotion, and assignment of staff shall be made without discrimination against any person. We welcome requests for reasonable accommodations for disabilities during the selection process. Information on how to request accommodations will be provided during the application process.
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