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Bank Data Analytics Jobs in Georgia (NOW HIRING)

Bank, we're on a journey to do our best. Helping the customers and businesses we serve to make ... The Infrastructure Data Analytics Engineer is responsible for acquiring, transforming, integrating ...

Lead Data Engineer

Alpharetta, GA · On-site

$111K - $134K/yr

... for analytics - semantic layers, metric definitions, and reconcilable outputs Security and ... Go Bankers, Go. Employment Type: FULL_TIME

Lead Data Engineer

Alpharetta, GA · On-site

$111K - $134K/yr

... for analytics - semantic layers, metric definitions, and reconcilable outputs Security and ... Go Bankers, Go. Employment Type: FULL_TIME

Data Analyst- South Bank, QLD Apply now Refer a friend Job no: 531911 Brand: Leisure* Work type ... Partner with Finance, Operations, BI, and Data teams to deliver business value through analytics

Tracks fraud data for reporting needs. Fosters productive relationships across the Bank and with ... Master's degree (MBA, Analytics, Data Science, Finance, or related discipline). * Experience ...

Tracks fraud data for reporting needs. Fosters productive relationships across the Bank and with ... Master's degree (MBA, Analytics, Data Science, Finance, or related discipline). * Experience ...

Data & Insights Lead - Loyalty- South Bank, QLD Apply now Refer a friend Job no: 531885 Brand ... Drive adoption of analytics outputs and recommendations to improve loyalty program performance and ...

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Bank Data Analytics information

What is bank data analytics?

Bank data analytics is the process of collecting, processing, and analyzing large volumes of data generated by banking transactions and operations. It helps banks gain insights into customer behavior, detect fraud, manage risks, and improve decision-making. By leveraging advanced analytical tools and techniques, banks can enhance customer experiences, increase efficiency, and develop data-driven strategies for growth. Bank data analytics professionals work with big data, machine learning, and statistical models to extract meaningful patterns and support business objectives.

How does a bank data analytics professional typically collaborate with other departments within a financial institution?

Bank Data Analytics professionals work closely with various departments such as risk management, marketing, compliance, and IT. They translate complex data sets into actionable insights, guiding strategic decisions and helping teams understand customer behavior, detect fraud, and ensure regulatory compliance. Regular cross-functional meetings and project-based collaborations are common, allowing analytics professionals to align data-driven recommendations with business goals and operational needs. This collaborative structure enhances communication, streamlines workflow, and maximizes the value of data across the organization.

What are the key skills and qualifications needed to thrive as a bank data analytics professional, and why are they important?

To thrive as a Bank Data Analytics professional, you need strong analytical skills, proficiency in statistics, and a solid background in finance or economics, often supported by a relevant degree. Expertise in data analysis tools such as SQL, Python, R, and experience with business intelligence platforms like Tableau or Power BI, as well as knowledge of data governance frameworks, is highly valued. Strong problem-solving abilities, attention to detail, and effective communication help translate complex data insights into actionable recommendations for stakeholders. These skills are crucial for driving data-informed decisions that enhance financial performance and risk management in the banking sector.

What is the difference between Bank Data Analytics vs Bank Data Analyst?

AspectBank Data AnalyticsBank Data Analyst
Required SkillsData analysis, statistical modeling, programming (SQL, Python)Data analysis, reporting, basic statistical skills
Work EnvironmentData teams, analytics departments within banksBank branches, finance departments, risk management teams
CertificationsData analytics certifications, SQL, Python coursesFinance or banking certifications, possibly data skills
Industry UsageFocus on developing analytics models and insightsFocus on interpreting data for decision-making

Bank Data Analytics involves advanced data modeling and technical skills to develop insights, while a Bank Data Analyst primarily interprets data to support banking operations. Both roles require analytical skills, but Bank Data Analytics is more technical and model-driven, whereas Bank Data Analyst focuses on reporting and data interpretation within banking environments.

What does a bank data analyst do for a bank?

A bank data analyst collects, processes, and analyzes financial data to identify trends, improve decision-making, and support risk management. They use tools like SQL, Excel, and data visualization software to interpret large datasets and provide insights to enhance banking operations and compliance.

What cities in Georgia are hiring for Bank Data Analytics jobs?

Cities in Georgia with the most Bank Data Analytics job openings:

Infographic showing various Bank Data Analytics job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 1% Temporary, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Banking Data & Analytics SME

Atlanta, GA

Tier4 Group
IT Services • 51 - 200 employees

Full-time

Posted yesterday

New


Job description

Location: Atlanta, GA metro area
6+ contract (likely extension)
Position: Banking Data & Analytics Subject Matter Expert (SME)
We are seeking a seasoned Banking Data & Analytics Subject Matter Expert (SME) to support a major banking transformation initiative. This individual will serve as the critical link between business stakeholders and technical teams, bringing deep expertise in retail and commercial banking while helping shape data-driven solutions that improve customer insights, profitability, reporting, growth, and risk management.

The ideal candidate combines strong banking domain knowledge with experience leading business and data initiatives, translating complex business needs into actionable requirements for data, analytics, and engineering teams.

Key Responsibilities
Banking Consulting & Stakeholder Engagement
Lead discovery sessions and workshops with executives, business leaders, product owners, and operational teams.
Provide expertise across retail and commercial banking products, processes, customer journeys, and performance metrics.
Identify key business challenges, opportunities, KPIs, and analytical use cases.
Challenge assumptions and recommend best practices based on banking industry experience.
Partner with stakeholders to prioritize initiatives based on business value, data readiness, and risk considerations.
Business & Data Translation
Translate business goals into detailed data, reporting, and analytics requirements.
Define KPI calculations, business rules, dimensional models, data quality standards, and reporting definitions.
Work closely with data architects, engineers, BI developers, and analytics teams to develop trusted business-ready data assets.
Support Customer 360, reporting, profitability, growth, and operational analytics initiatives.
Ensure data models and reporting platforms support current business needs and future AI-driven capabilities.
Required Qualifications
12+ years of experience in Business Analysis, Product Ownership, Consulting, or related disciplines.
5+ years of direct banking industry experience supporting U.S. financial institutions.
Proven success delivering banking data, analytics, reporting, Customer 360, data warehouse, or lakehouse initiatives.
Strong understanding of retail and commercial banking products, operations, and performance metrics.
Demonstrated ability to facilitate executive-level workshops and stakeholder discussions.
Experience gathering requirements and translating business needs into technical specifications.
Strong communication, presentation, and stakeholder management skills.
Working knowledge of Agile methodologies, user acceptance testing, and change management processes.
Preferred Qualifications
Experience working with regional or mid-sized banks.
Microsoft Fabric, Azure Data Services, Power BI, SQL, or Salesforce experience.
Exposure to data governance, metadata management, and master data initiatives.
Experience defining banking metrics related to deposits, lending, profitability, customer relationships, churn, cross-sell, and executive reporting.
CBAP, PMI-PBA, CSPO, or other relevant certifications.