Head of Investment Risk and Analytics

SEI

. Design and build the Investment Management Unit’s consolidated investment oversight application .

Posted 10/13/2026full-timeRemote • Pennsylvania • United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in quantitative investment management, risk analytics, and data architecture, with a strong focus on building and integrating investment oversight applications. Proven ability to lead teams, develop talent, and communicate complex analytics to institutional clients.

Highest-signal resume keywords

Quantitative Investment ManagementRisk Analytics LeadershipData Architecture and GovernancePython, SQL, JavaScript, R, MATLABBloomberg PORT/PREP, Snowflake, Postgres

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Quantitative Investment ManagementRisk AggregationPortfolio ConstructionModel DocumentationData Pipeline DevelopmentInvestment Decision ProcessesAI IntegrationPerformance AttributionData GovernanceAnalytics Team Leadership

Soft Skills

Expert Communication SkillsTeam DevelopmentClient EngagementCollaborationCredibility with Senior Leaders

Tools & Technologies

Bloomberg PORT/PREPSnowflakePostgresAladdinAxiomaMSCI BarraOneCloud Data WarehousingWeb Application FrameworksInvestment PlatformsAI-Assisted Development Tools

Certifications & Qualifications

Graduate Degree in Quantitative DisciplineCFA Charterholder

Industry Keywords

Investment ManagementPortfolio ManagementAsset AllocationInstitutional SolutionsMulti-Asset DisciplinesModel-Risk ReviewALM/LDIPensionSurplus RiskOutcome-Oriented Mandates

Tech Stack

Tools & technologies

CloudJavaScriptPostgresPythonSQL

About the role

Key responsibilities & impact

Design and build the Investment Management Unit’s consolidated investment oversight application
Integrate analytics from investment, OCIO, and manager research teams, third-party platforms, and internally built applications
Build automated data pipelines, reconciled security and position masters, vendor-data governance, and auditable data lineage
Design a drillable CIO oversight view covering portfolio risk, liquidity risk, factor exposures, counterparty risk, implementation quality, performance attribution, model status, and decision history
Establish standards for risk aggregation, limits monitoring, and exception escalation
Embed LLM-driven analysis, retrieval, synthesis, monitoring, and decision-support features into investment applications
Partner with AI leadership to align investment AI adoption with the enterprise AI roadmap
Connect quantitative equity, fixed income, macro, OCIO, and manager research teams through shared platforms and joint development
Partner with the Chief Data Officer on data architecture and governance
Represent the investment organization within SEI’s enterprise data and AI leadership group
Ensure major platform initiatives have named partners outside the immediate team
Represent SEI’s investment risk and analytics capability in RFPs, due diligence meetings, webinars, and client reviews
Explain portfolio, factor, ALM/LDI, and scenario analytics clearly and commercially
Lead, develop, and shape a team spanning quantitative analytics, data engineering, and application development
Recruit hybrid talent combining investment domain knowledge with hands-on engineering ability
Represent SEI’s investment analytics perspective through research, publication, and industry engagement

Requirements

What you’ll need

15+ years in quantitative investment management, portfolio management, asset allocation, managed volatility, institutional solutions, or related multi-asset disciplines
Direct accountability for risk taking and investment outcomes at scale
Experience leading quantitative research or analytics teams
Experience hiring and developing technical investment talent
Experience owning model documentation and responding to model-risk review
Experience improving portfolio construction and investment decision processes
Expert communication skills for presenting complex risk analytics to institutional clients
Demonstrated record of personally designing and building front-office platforms used by portfolio managers, CIOs, investment teams, and distribution partners
Experience aggregating positions, risk, and analytics across a global investment platform from multiple vendor and internal engines
Experience with Bloomberg PORT/PREP, Snowflake, Postgres, Aladdin, Axioma, MSCI BarraOne, or similar systems
Hands-on technical depth in Python, SQL, JavaScript, R or MATLAB, relational databases, cloud data warehousing, web application frameworks, institutional risk platforms, and portfolio analytics systems
Daily personal use of AI-assisted and agentic development tools
Experience integrating large language models via API into investment applications
Credibility with senior investment leaders, portfolio managers, research teams, engineers, enterprise data partners, and client-facing teams
Experience modeling public and private assets for complex institutional clients, including OCIO, insurance general account, pension, ALM/LDI, surplus risk, target-date, and outcome-oriented mandates
Graduate degree in a quantitative discipline
CFA charterholder and published research preferred
Published or public thought leadership strongly preferred

Benefits

Comp & perks

Comprehensive care for physical and mental well-being
Strong retirement plan
Tuition reimbursement and education assistance
Support for working parents
Flexible Paid Time Off (PTO)
Healthcare: medical, dental, vision, prescription, wellness, EAP, FSA
Life and disability insurance, with premiums paid for base coverage
401(k) match
Commuter benefits
Up to 11 paid holidays per year
21 days PTO per year, pro-rated for new hires, increasing over time
Paid parental leave
Back-up childcare arrangements
Paid volunteer days
Discounted stock purchase plan
Investment options
Access to employee networks