Support applied AI and quantitative research within private markets.
Compensation
Salary: $30/hour
Responsibilities
Support applied AI and quantitative research using StepStone’s proprietary data and institutional knowledge to identify investment signals, performance drivers, portfolio trends, and emerging risks across private markets.
Apply statistical, econometric, machine learning, and natural-language processing methods to structured and unstructured information, with an emphasis on producing robust, explainable, and economically intuitive findings.
Work with investment, data, and technology stakeholders to translate investment questions into analytical approaches and connect research findings to practical applications in investment selection, portfolio construction, monitoring, benchmarking, and risk assessment.
Document research approaches, assumptions, findings, and limitations, and communicate conclusions clearly to both technical and non-technical audiences.
Requirements
Bachelor's or master's degree in Mathematics, Statistics, Econometrics, Computer Science, Engineering, Data Science, Finance, Economics, or a related quantitative field
As a Senior Analyst specialising in data, analytics and AI in our Digital team, part of Consulting, you’ll turn complex data into practical solutions and clear insights for clients and project teams.
Responsibilities
Gather and clarify business requirements
Shape the right data, analytics or AI approach and deliverables
Prepare, transform and analyse datasets to develop dashboards, reports, analytical models or AI-enabled solutions
Senior professional support for Overhead Lines Design Modelling Standards team, developing and maintaining modelling standards, workflows, dashboards and automation tools.
Locations (2)
Dublin, Dublin, Ireland
Ireland
Compensation
€59,980 - €70,654 per annum
Responsibilities
Support the Team Lead in developing and maintaining standards, controlled workflows and supporting tools for overhead line engineering design modelling software, including PLS-CADD and related applications.
Structure, validate and maintain controlled modelling inputs and reference content, including structure, material and conductor libraries, criteria files, templates, survey inputs and model metadata.
Develop dashboards, reports and assurance controls covering model completeness, compliance with modelling standards, revision status, use of approved baselines and agreed modelling-governance indicators.
Develop and support automated workflows for model creation, checking, approval, publication, metadata capture, controlled issue and project handover of engineering modelling records.
Own the design and build of a sanction-grade, real-time risk decisioning engine that blends rules and ML scoring into a single decision API used across Equiti’s products.
Deliver a self-serve rules engine so risk analysts can author, test and roll back rules without an engineering deploy.
Build velocity, limits and enforcement controls that are highly available and fully auditable, so every decision can be traced for regulators and auditors.
Own the device and session intelligence layer, including build-vs-buy decisions.
Partner with Data Science to deploy and govern fraud models (account takeover, synthetic identity, mule detection, payment fraud, promo abuse), with confirmed outcomes feeding back into rules and models.
Requirements
Degree in a relevant technical, risk or quantitative discipline, or equivalent practical experience.
Lead data engineering and automation initiatives for CFOs and finance teams, designing data architectures, pipelines, and dashboards to improve financial reporting and decision-making.
Compensation
A reasonable estimate of the current range is $87,000.00 - $195,000.00 . This role is also anticipated to be eligible to participate in an annual bonus plan.
Responsibilities
Design, build, and implement data architectures, including data warehouses, data lakes, and ETL/ELT pipelines
Develop automated data pipelines to consolidate financial and operational information
Implement system integrations using iPaaS solutions such as Boomi, Workato, MuleSoft, Azure Logic Apps
Build and implement financial dashboards using Power BI, Tableau
Work with CFOs and finance leaders to translate business requirements into technical solutions
Requirements
Bachelor's degree in Computer Science, Information Systems, Data Analytics, Finance, Accounting, or a related field
Lead Software Engineer responsible for designing, building, and operating enterprise finance solutions across cloud ERP platforms, integrations, and data pipelines, applying AI and automation to improve engineering productivity and finance operations.
Responsibilities
Define technical architecture across cloud ERP, integration, and data platforms
Design, build, and operate integrations connecting Workday and other finance applications with Salesforce
Develop solutions using ERP development, MuleSoft/API engineering, or data engineering
Build reliable APIs, event‑driven integrations, data pipelines, and transformations
Lead complex troubleshooting across application, integration, and data layers
Support an exciting National Security mission to position NGA as the enterprise and community GEOINT data provider, improving the way analysts, customers, and end users access, discover, stage, link, produce, re-integrate, and deliver intelligence.
Compensation
$140,000 -$170,000
Responsibilities
Design, build, test, and maintain data pipelines and ETL/ELT workflows for analytics, reporting, and mission operations
Develop and maintain API connectors and integrations that ingest data from internal platforms and external services
Create and improve data models and processing workflows to meet established performance, scale, and reliability needs
Implement data validation, quality checks, monitoring, and documentation for assigned data products and workflows
Work with mission stakeholders, analysts, and architects to clarify requirements and deliver maintainable technical solutions
Requirements
Bachelor’s or master’s degree in computer science, information systems, engineering, mathematics, or a related field; equivalent education and experience may be considered
Lead the development, implementation and operation of analytics to monitor generation performance and support asset reliability and maintenance planning.
Compensation
Competitive Salary *401k Savings plan w/ company matching * Pension plan * Paid time off* Paid Holiday time * Medical, Prescription Drug, & Dental Coverage *Tuition Assistance Program * Employee Assistance Program * Wellness Programs * On-site Fitness Centers * Bonus Plan and more!
Responsibilities
Lead the development, implementation and operation of Analytics to monitor generation performance
Lead the development of analytics using Asset Management and formal reliability engineering
Lead the vision for analytics at the generating fleet level
Lead development of fleet level analytics centrally located on Power BI
Lead development of analytics for the support of performance reporting
Requirements
Bachelor’s degree in Engineering, Data Science, Applied Mathematics or Statistics
Lead complex digital fraud programs within Cybersecurity & Digital Risk, translating fraud strategy into coordinated roadmaps, funded initiatives and measurable business outcomes.
Locations (2)
Chicago, Illinois, United States
United States
Compensation
The base pay range for this role is $102,220.00 to $133,194.00. The base salary range/hourly rate listed is dependent on job-related, factors such as experience, education, and skills. This position is also eligible for bonus and/or long-term incentive compensation awards.
Responsibilities
Translate enterprise fraud strategy into integrated roadmap
Manage initiative intake, prioritization, sequencing and portfolio governance
Lead digital fraud initiatives from business case to launch and benefits realization
Coordinate fraud and identity-risk assessments and control requirements
Manage program funding, forecasts, vendor and platform governance
Requirements
Bachelor's degree in Business, Program or Project Management, Cybersecurity, Information Systems, Computer Science, Analytics, Risk Management or related field
Work with engineering specialists and designers to translate technical modelling requirements into practical model structures, templates, validation rules, reports and repeatable design-support processes.
Requirements
Level 8 degree in Engineering, Data Science, Computer Science, Information Systems, Analytics, Mathematics, Physics or another relevant technical discipline, or an equivalent combination of qualification and relevant experience.
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