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Data Analytics Director Jobs in Raleigh, NC (NOW HIRING)

No direct reports. JOB DIMENSIONS The Sr. Financial Analyst works across various parts of the ... Data mining and development and implementation of automated solutions to improve Finance processes ...

No direct reports. JOB DIMENSIONS The Sr. Financial Analyst works across various parts of the ... Data mining and development and implementation of automated solutions to improve Finance processes ...

Sr. Financial Analyst (Data Analytics) Job

Cary, NC · On-site

$79K - $98K/yr

No direct reports. JOB DIMENSIONS The Sr. Financial Analyst works across various parts of the ... Data mining and development and implementation of automated solutions to improve Finance processes ...

About the Role : The Director, Data Sciences raises data-driven decision making of a function ... Data Analysis and Modeling : Oversee advanced data analysis, modeling, and machine learning to ...

About the Role : The Director, Data Sciences raises data-driven decision making of a function ... Data Analysis and Modeling : Oversee advanced data analysis, modeling, and machine learning to ...

This position will report to the Director, Data/Analytics/AI (D&A Digital Marketing) and is based in Raleigh, NC (hybrid eligible). Key Responsibilities: * Own end to end delivery of US Commercial ...

This position will report to the Director, Data/Analytics/AI (D&A Digital Marketing) and is based in Raleigh, NC (hybrid eligible). Key Responsibilities: * Own end to end delivery of US Commercial ...

Learning Analytics Analyst Duration: Fixed-term contingent role (Target End Date: 03/28/2027 ... We specialize in Contract and Contract to Permanent roles across many industries and have direct ...

Data Strategy-Senior Manager

Raleigh, NC · On-site

$124K - $280K/yr

In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract ... Direct the team through complexity, demonstrating composure through ambiguous, challenging and ...

LexisNexis is a part of RELX, a global provider of information-based analytics and decision tools ... Leading small- to medium-sized teams (direct or indirect). Qualifications : Required : • Possess ...

Ten or more years of experience across marketing data, MarTech, analytics, or digital ... The Director will define and lead a modern customer data strategy and will be responsible for the ...

Ten or more years of experience across marketing data, MarTech, analytics, or digital ... The Director will define and lead a modern customer data strategy and will be responsible for the ...

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Showing results 1-20

Data Analytics Director information

See Raleigh, NC salary details

$69K

$153.7K

$237.7K

How much do data analytics director jobs pay per year?

As of Jun 10, 2026, the average yearly pay for data analytics director in Raleigh, NC is $153,702.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,900.00 and $175,000.00 per year, depending on experience, location, and employer.

What is the difference between Data Analytics Director vs Data Scientist?

AspectData Analytics DirectorData Scientist
Required CredentialsBachelor's or Master's in Data Science, Business, or related field; often requires leadership experienceBachelor's, Master's, or Ph.D. in Data Science, Statistics, or related field; technical expertise in modeling
Work EnvironmentLeadership role overseeing analytics teams, strategic planning, and project managementHands-on data analysis, model development, and algorithm implementation
Employer & Industry UsageUsed in corporate, finance, healthcare, and tech sectors for strategic decision-makingCommon in tech, research, and analytics firms for developing data models and insights

The main difference is that a Data Analytics Director focuses on leading analytics teams and strategic initiatives, while a Data Scientist is primarily involved in technical data modeling and analysis. Both roles require strong analytical skills, but the Director role emphasizes leadership and business strategy.

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

To thrive as a Data Analytics Director, you need advanced expertise in data analysis, statistical modeling, and business intelligence, typically supported by a relevant degree and significant experience in analytics leadership. Familiarity with tools such as SQL, Python, R, and data visualization platforms like Tableau or Power BI, along with knowledge of data governance and cloud technologies, is essential. Exceptional leadership, strategic thinking, and communication skills help drive cross-functional collaboration and translate data insights into business value. These competencies are crucial for guiding analytic strategy, ensuring data-driven decision-making, and maximizing organizational impact.

What does a Data Analytics Director do?

A Data Analytics Director is responsible for overseeing the data analytics department within an organization. They lead teams that collect, process, and interpret large sets of data to provide actionable insights for business decision-making. This role involves developing data strategies, implementing analytical tools and techniques, and ensuring data quality and security. The Data Analytics Director also collaborates with other departments to align analytics initiatives with organizational goals and drive data-driven growth.

What are some common challenges faced by a Data Analytics Director when aligning analytics initiatives with business objectives?

A Data Analytics Director often encounters challenges in ensuring that analytics projects are closely aligned with the strategic goals of the organization. This includes bridging communication gaps between technical teams and business stakeholders, prioritizing projects with the highest business impact, and managing expectations regarding what data analytics can deliver. Additionally, it can be challenging to foster a data-driven culture across departments and to secure buy-in for data initiatives. Effective collaboration, clear communication, and a strong understanding of both analytics and business priorities are essential to overcome these hurdles.
What are the most commonly searched types of Data Analytics jobs in Raleigh, NC? The most popular types of Data Analytics jobs in Raleigh, NC are:
What are popular job titles related to Data Analytics Director jobs in Raleigh, NC? For Data Analytics Director jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Data Analytics Director jobs in Raleigh, NC look for? The top searched job categories for Data Analytics Director jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Data Analytics Director jobs? Cities near Raleigh, NC with the most Data Analytics Director job openings:
Infographic showing various Data Analytics Director job openings in Raleigh, NC as of June 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $153,702 per year, or $73.9 per hour.
Senior Manager, Data, Analytics & AI

Senior Manager, Data, Analytics & AI

ACA Group

Durham, NC • On-site

Other

Posted 27 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.