Senior Manager, Data Analytics and AI - Global Regulatory Advisory will build and scale the data infrastructure, analytics, and AI-enabled automation that power how ACA's Global Regulatory Advisory ...
Senior Manager, Data Analytics and AI - Global Regulatory Advisory will build and scale the data infrastructure, analytics, and AI-enabled automation that power how ACA's Global Regulatory Advisory ...
The role will also design data infrastructure to support AI and advanced analytics use cases. Qualifications * Proven experience in building enterprise data lakes and integration platforms in a CRO ...
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The role will also design data infrastructure to support AI and advanced analytics use cases. Qualifications * Proven experience in building enterprise data lakes and integration platforms in a CRO ...
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ACA Group is a leader in Global Regulatory Advisory, seeking a Senior Manager for Data Analytics and AI to build and scale their data infrastructure and analytics capabilities. This role involves ...
ACA Group is a leader in Global Regulatory Advisory, seeking a Senior Manager for Data Analytics and AI to build and scale their data infrastructure and analytics capabilities. This role involves ...
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From developing go-to-market strategies and building foundational data analytics infrastructures to leveraging artificial intelligence to improve customer insights and engagement, Beghou helps life ...
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Data Infrastructure And Analytics information
See Raleigh, NC salary details
$148.7K - $153.1K
8% of jobs
$153.1K - $157.4K
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$160.9K is the 25th percentile. Wages below this are outliers.
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The median wage is $172.8K / yr.
$170.4K - $174.7K
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$174.7K - $179K
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$184.7K is the 75th percentile. Wages above this are outliers.
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$187.7K - $192K
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9% of jobs
$148.7K
$173.8K
$196.4K
How much do data infrastructure and analytics jobs pay per year?
Is AI replacing data analysts?
What is the highest paying job in data analytics?
What is the difference between Data Infrastructure And Analytics vs Data Engineer?
| Aspect | Data Infrastructure And Analytics | Data Engineer |
|---|---|---|
| Primary Focus | Building data systems, managing data infrastructure, and enabling analytics | Designing, constructing, and maintaining data pipelines and storage solutions |
| Skills & Certifications | Data management, SQL, cloud platforms, analytics tools | Programming (Python, Java), ETL, database systems, cloud services |
| Work Environment | Collaborates with data analysts, scientists, and business teams | Works closely with data architects and software engineers |
| Industry Usage | Used across industries for data-driven decision making | Primarily in tech, finance, and large enterprises with complex data needs |
While both roles involve working with data systems, Data Infrastructure And Analytics focuses on creating and managing the infrastructure that enables data analysis, whereas Data Engineers primarily build and maintain the data pipelines and storage solutions that support these analytics. Understanding these distinctions helps organizations assign the right skills to each role.
What is data infrastructure and analytics?
Is a data analyst a well paid job?
Job description
Senior Manager, Data Analytics and AI - Global Regulatory Advisory will build and scale the data infrastructure, analytics, and AI-enabled automation that power how ACA's Global Regulatory Advisory business operates. Partnering closely with the Head of Operations, Global Regulatory Advisory, and business, finance, and technology leaders across multiple advisory segments, this role will unify fragmented operational, project, client, and financial data into a reliable single source of truth. The role will also deliver executive-ready reporting on utilization, profitability, bookings-to-revenue conversion, and other core KPIs. Success is defined by measurable improvements in data quality, reporting speed and consistency, and the adoption of repeatable, data-led operating rhythms that increase efficiency, margin, and client delivery excellence.
The Opportunity:
ACA Group is building the operational backbone for its next phase of growth-and this role is at the center of it. - Strategy & Operations, you will partner directly with the Head of Operations for ACA's Global Regulatory Advisory business to architect, build, and scale the data infrastructure and analytics capabilities that power how we run, measure, and grow a multi-segment, ~$100M+ advisory practice.
Today, our US Regulatory business spans Private Funds, Fund Officers, Broker Dealer, and Wealth-each with its own delivery model, client base, and operational rhythm. Your mandate is to build and maintain a data and analytics backbone that helps operationalize and systematize how we analyze disparate data at scale, maximize business efficiency and profitability, and create a unified data schema that empowers both practice-level insight and enterprise-level clarity-while maintaining an exceptional client experience for our delivery teams.
You will own the design and implementation of scalable data systems, AI-driven automation, and advanced analytics that enable leadership to manage the business through a single, data-led operating lens-from utilization and scorecard tracking to project profitability, revenue recognition, and management reporting. This is not a support role. This is a builder's role-high autonomy, high impact, and a direct line to the decisions that shape how ACA's largest advisory business operates and scales.
If you're energized by the idea of turning messy, real-world operational data into clean, automated, decision-grade intelligence-and you want to do it inside a fast-moving, PE-backed GRC leader-this is your opportunity.
Job Duties:
Design and build scalable data architecture to unify fragmented product, project, billing, and client engagement data across multiple business segments and legacy systems (PSA tools, CRM, Deltek, Power BI, finance platforms, Workday, manual spreadsheets).
Develop and deploy AI and automation solutions to reduce manual rework in operational workflows, including capacity and utilization reporting, project profitability analysis, data aggregation, cross-functional data migrations, and client engagement hygiene tracking.
Build and maintain advanced dashboards and analytics tools using Power BI, Python, and Excel to deliver real-time, decision-grade visibility into key operational KPIs such as billable utilization, project profitability, cost-to-serve drivers, bookings-to-revenue conversion, and termination/churn analytics.
Integrate disparate data sources across the enterprise (Salesforce, PSA/project management tools, Power BI, SharePoint, finance systems) via APIs and automated ETL pipelines to establish a reliable single source of truth for operational reporting.
Partner cross-functionally with Business Unit Leaders (Private Funds, Fund Officers, Broker Dealer, Wealth), FP&A, Human Resources, and Technology to ensure data definitions, reporting cadences, and KPI frameworks are standardized and aligned to the firm's financial and operational rhythms.
Support the development and automation of management reporting cycles, including quarterly business reviews, monthly financial reviews, and board-level materials-transforming manual, labor-intensive reporting into repeatable, data-driven operating systems.
Quantify operational constraints and opportunities through rigorous analysis-identifying where execution mechanics (data classification errors, billing discrepancies, non-billable capacity inefficiencies) are creating drag on margin and growth, and recommending data-backed improvements.
Prototype and scale AI agents and tools (e.g., Copilot-based automation, custom Python scripts, LLM-assisted workflows) to accelerate reporting, analysis, and decision-making across the US Regulatory team.
Champion a data-led culture within the operations function by establishing SOPs for data governance, reporting standards, and analytics best practices that can be replicated across ACA's global advisory businesses.
Required Education and Experience:
- Bachelor's degree, preferably in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, Finance, or a related discipline.
- At least 7-10 years of progressive experience in data analytics, quantitative analysis, business intelligence, or quantitative software/application development, ideally within professional services, financial services, or an advisory environment.
- Advanced proficiency in Python for data manipulation, automation, and analysis (pandas, NumPy, scripting, API integrations).
- Proven expertise leveraging AI tools (e.g., Copilot, Claude) in an enterprise environment to drive scalable efficiencies (automation, agent-building, workflow optimization, reporting, QC analysis).
- Expert-level skills in Microsoft Excel (complex modeling, Power Query, VBA/macros) and Power BI (DAX, data modeling, dashboard design, publishing).
- Demonstrated experience building APIs and automated data pipelines/ETL processes across enterprise systems.
- Proven ability to work with large, complex, disparate datasets-cleaning, reconciling, and structuring data into reliable analytical outputs.
- Experience partnering cross-functionally with senior business leaders, finance teams, and technology stakeholders to translate operational needs into analytical solutions.
Preferred Education and Experience:
- Experience in a high-growth, private equity-backed, or professional services environment.
- Familiarity with GRC (governance, risk, and compliance), regulatory advisory, or financial services operations.
- Hands-on experience with AI/ML tools, large language models, or AI agent development (e.g., Microsoft Copilot, OpenAI APIs, Claude).
- Experience with Salesforce reporting, PSA/project management platforms, and financial planning tools.
- Master's degree in a quantitative discipline, MBA, or equivalent advanced training.
- Prior experience building or scaling a data/analytics function within a complex organization.
Required Skills and Attributes:
- Builder's mindset: thrives in ambiguity and creates structured, scalable solutions from scratch.
- Strong operational intuition: connects data to business decisions and understands impact on outcomes.
- High ownership: takes initiative and drives work from concept through delivery.
- Cross-functional fluency: effectively translates between business, finance, and technical stakeholders.
- Precision and rigor: prioritizes data quality, consistency, and analytical integrity.
- Intellectual curiosity: stays current on emerging tools, especially in AI, automation, and data engineering.
- Excellent communication skills: able to present complex insights in clear, executive-ready formats.
About ACA Group
Sourced by ZipRecruiter
Industry
Finance and insurance
Company size
501 - 1,000 Employees
Headquarters location
New York, NY, US
Year founded
2002