Team Lead, Product Operations, ICE Climate

Job Description

Job Purpose

ICE Climate Operations supports ICE's Climate Risk Data business, covering physical climate risk, transition risk, nature-related risk, and avoided emissions across public and private companies, sovereigns, and structured finance assets such as mortgage-backed and municipal securities. The Physical Risk team runs the geospatial research and quality assurance function behind this coverage, identifying and validating corporate and sovereign asset locations against wildfire, flood, hurricane, and extreme-temperature exposure for ICE's global geospatial risk platform.

 

Lead the operational delivery and continuous improvement of Physical Risk data projects within ICE Climate Operations. The role manages and develops a team of analysts responsible for asset-location research, geospatial validation, structured quality assurance, and project delivery. It combines people leadership with hands-on oversight of complex research and QA, ensuring data is accurate, complete, traceable, and delivered in line with product and client priorities.

 

The team leader is the primary operational contact for Physical Risk workstreams and coordinates closely with Product, R&D, Engineering, Analytics, and Data Quality teams. The role is expected to translate evolving requirements into clear work plans, maintain visibility of progress and risks, and build the team's ability to support product improvements and respond to data-related queries with increasing independence.

 

Responsibilities

• Team leadership and delivery management
  • Lead, coach, and develop a team of associates and senior associates, setting clear expectations for delivery, quality, accountability, and professional growth.
  • Convert business and project priorities into practical work plans, allocate resources across concurrent workstreams, and adjust assignments as priorities change.
  • Monitor milestones, productivity, quality, and turnaround times; identify delivery risks early and implement recovery actions.
  • Conduct regular one-to-one discussions, goal setting, performance reviews, and development planning; support recruitment, onboarding, and succession readiness.
  • Act as the first point of escalation for operational blockers, quality concerns, scope ambiguity, and resourcing conflicts.
• Physical risk project and product support
  • Lead operational support for Physical Risk initiatives, including industrial and mine location QA, high-materiality asset review, corporate mapping, location weighting, and damage-function research across corporate, sovereign, and private-company asset classes.
  • Coordinate delivery with Product and R&D stakeholders, clarify objectives and acceptance criteria, maintain project status and dependencies, and ensure outputs are usable for downstream product or model development.
  • Keep the team focused on work that improves the quality and coverage of Physical Risk products, including continuous QA of critical asset data and on-demand QA or updates for client-driven requirements spanning wildfire, flood, hurricane, and extreme-temperature exposure.
  • Build sufficient product and methodology knowledge within the team to support data samples, stakeholder queries, and issue investigation with reduced dependency on Product teams.
• Research, geospatial data, and quality assurance
  • Oversee research to identify, classify, map, and validate corporate asset locations, ownership relationships, operational status, facility type, coordinates, and materiality indicators.
  • Ensure consistent use of authoritative internal data, third-party datasets, company disclosures, mapping platforms, satellite imagery, and documented public sources.
  • Review complex or high-risk discrepancies, confirm source traceability, approve final outputs, and direct root-cause analysis and corrective actions.
  • Oversee QA controls for completeness, coordinate accuracy, classification, duplication, status, source evidence, and conformity with approved methodologies and due-diligence standards.
  • Ensure project outputs are documented, reproducible, and ready for ingestion, analytics, model research, or client delivery as applicable.
• Data, reporting, and operational governance
  • Use SQL and BigQuery to retrieve, join, analyze, and validate entity and location datasets; use advanced Excel and reporting tools to manage and communicate delivery performance.
  • Maintain concise dashboards and status reporting covering scope, milestones, quality, throughput, risks, dependencies, and decisions required.
  • Establish clear operating procedures, research playbooks, source hierarchies, QA checklists, and hand-off criteria; keep documentation current as requirements evolve.
  • Support audits, internal reviews, release validation, production issue analysis, and governance activities relevant to Physical Risk data operations.
• Process improvement, automation, and capability building
  • Identify recurring data and workflow issues and implement scalable improvements that reduce manual effort, rework, and turnaround time without weakening control quality.
  • Promote responsible use of AI-assisted research, automated validation, and smart workflows, with human verification and clear evidence retained for material decisions.
  • Develop team capability in Physical Risk methodology, corporate structures and identifiers, GIS and mapping, asset materiality, SQL/BigQuery, QA, and relevant internal platforms.
  • Create a collaborative learning environment through structured training, calibration sessions, knowledge sharing, and review of complex cases.

 

Knowledge and Experience

• Bachelor's or Master's degree in Geography, Geospatial Science, Environmental Science or Planning, Data Science, Engineering, or a related discipline.
• 6+ years of relevant experience in data operations related to geospatial or location data, GIS research, including experience leading people or project delivery.
• Demonstrated ability to manage priorities, resources, quality, and stakeholder expectations in a data-intensive operational environment.
• Working knowledge of corporate entity structures, asset-location data, geospatial concepts, mapping tools, and research-based verification.
• Proficiency in SQL, Python, and advanced Excel; practical experience querying and analyzing large datasets. Experience with BigQuery is strongly preferred.
• Strong analytical judgment, attention to detail, documentation discipline, and ability to resolve ambiguous or conflicting evidence.
• Clear written and verbal communication, with the ability to present status, risks, recommendations, and decisions to technical and non-technical stakeholders.

 

Preferred Knowledge and Experience

• Experience supporting Physical Risk, climate risk, catastrophe modelling, asset-level analytics, or commercial geospatial data products.
• Exposure to facility materiality, industrial assets, mines, utilities, damage-function or historical-loss research, and third-party location datasets.
• Experience with Power BI or similar reporting tools, workflow automation, and AI-assisted research or validation processes.
• Familiarity with data governance, audit controls, client data samples, and cross-functional product delivery.