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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Manager, Data, Analytics & AI - **Company:** ACA Group - **Location:** Pittsburgh, PA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Microsoft Excel, Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Spreadsheets, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Normalization, Python (Programming Language), Project Management Software, NumPy, Power BI, Salesforce.Com, Microsoft SharePoint, Software Engineering, Data Processing, Scripting, Data Classification, Macros, Microsoft Power Automate, Large Language Models, Powerquery, Pandas, Build Management, Information Technology, Vba Programming Language, Data Analytics, Machine Learning Operations, Virtual Agents, Api Design, Data Pipelines, Api Management, Workday, Legacy Systems - **Published:** May 15, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=3f0702c4a09f8903 ## About the Role Do you have experience in VBA?, * 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., * 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. ## 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., * 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. ## Related Videos - [Vectorize all the things! 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