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Program Manager Data Analytics Jobs in Chattanooga, TN

... management. Strong SQL knowledge with complex queries including joins etc. Excellent skills in ... data analyst tool/IDQ Knowledge of XML and other databases like DB2, teradata and SQL. Experience ...

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Program Manager Data Analytics information

See Chattanooga, TN salary details

$35.1K

$97.8K

$143K

How much do program manager data analytics jobs pay per year?

As of Jun 21, 2026, the average yearly pay for program manager data analytics in Chattanooga, TN is $97,846.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,400.00 and $120,600.00 per year, depending on experience, location, and employer.

What is the difference between Program Manager Data Analytics vs Data Analyst?

AspectProgram Manager Data AnalyticsData Analyst
CredentialsBachelor's or Master's in Business, Data Science, or related fields; certifications like PMP or CAPM beneficialBachelor's in Statistics, Data Science, or related fields; certifications like Microsoft Data Analyst Associate helpful
Work EnvironmentOversees multiple projects, collaborates with cross-functional teams, manages stakeholdersAnalyzes data sets, creates reports, supports decision-making within teams
Industry UsageCommon in tech, finance, healthcare, and large organizationsWidely used across industries for data interpretation and reporting

The Program Manager Data Analytics focuses on managing multiple analytics projects and coordinating teams, while Data Analysts primarily analyze data and generate reports. Both roles require strong analytical skills, but the Program Manager has broader responsibilities in project oversight and stakeholder management.

Is 40 too late for data science?

For a Program Manager in Data Analytics, starting a career in data science at age 40 is feasible, as many skills such as statistical analysis, programming, and data visualization can be learned at any age. Experience in related fields and continuous learning through certifications or courses can enhance job prospects regardless of age.

Is AI replacing data analysts?

Program managers in data analytics oversee projects that often involve AI tools, but AI is not replacing data analysts; instead, it automates routine tasks, allowing analysts to focus on complex analysis and strategic insights. Data analysts' skills in interpreting data, storytelling, and domain knowledge remain essential, and proficiency with AI and machine learning tools enhances their effectiveness.

How does a Program Manager in Data Analytics typically collaborate with cross-functional teams?

As a Program Manager in Data Analytics, you will frequently work with data engineers, analysts, business stakeholders, and IT teams to drive analytics initiatives from conception to completion. This collaboration involves translating business objectives into technical requirements, ensuring clear communication between teams, and managing timelines and deliverables. Regular meetings, stakeholder updates, and agile project management practices are commonly used to keep everyone aligned and to adapt quickly to changing priorities. Building strong relationships across departments is essential for successfully delivering data-driven solutions.

Do program managers need data analytics skills?

Program managers in data analytics roles typically need skills in data analysis, visualization tools, and understanding of data-driven decision-making. These skills help them oversee projects that involve large datasets and ensure strategic goals are met efficiently.

What are the key skills and qualifications needed to thrive as a Program Manager in Data Analytics, and why are they important?

To thrive as a Program Manager in Data Analytics, you need strong project management skills, deep analytical expertise, and a background in statistics or computer science, often supported by a bachelor’s or master’s degree. Familiarity with analytics platforms (such as Tableau or Power BI), programming languages (like SQL or Python), and certifications like PMP or Agile are highly valuable. Exceptional communication, leadership, and stakeholder management skills help in aligning teams and translating complex data insights into actionable business strategies. These capabilities ensure successful delivery of analytics initiatives that drive informed decision-making and organizational growth.

What is a Program Manager in Data Analytics?

A Program Manager in Data Analytics is responsible for overseeing and coordinating multiple data analytics projects or initiatives within an organization. They work closely with data analysts, data scientists, and other stakeholders to ensure that data-driven projects align with business objectives, are delivered on time, and produce actionable insights. Their role includes strategic planning, resource allocation, risk management, and communication between technical teams and business leaders. Program Managers help bridge the gap between technical execution and organizational goals, ensuring that data analytics initiatives deliver measurable value.

Who earns more, a project manager or a data analyst?

A project manager typically earns more than a data analyst due to greater responsibilities, leadership requirements, and often higher levels of experience and certification. Project managers usually oversee entire projects, budgets, and teams, which contributes to higher compensation compared to data analysts who focus on data interpretation and reporting.
What job categories do people searching Program Manager Data Analytics jobs in Chattanooga, TN look for? The top searched job categories for Program Manager Data Analytics jobs in Chattanooga, TN are:
What cities near Chattanooga, TN are hiring for Program Manager Data Analytics jobs? Cities near Chattanooga, TN with the most Program Manager Data Analytics job openings:
Senior Manager, Data, Analytics & AI

Senior Manager, Data, Analytics & AI

ACA Group

Chattanooga, TN

Other

Posted 7 days ago


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:

  1. 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).

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.