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Weekend Data Analyst Fintech Jobs in Georgia (NOW HIRING)

Leverage expertise in data structures and algorithms to analyze and prepare data for modeling ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

Function The Data Scientist will play a critical role in designing, scaling, and operationalizing advanced analytics and machine learning solutions across the company's FinTech platforms. This role ...

Function The Data Scientist will play a critical role in designing, scaling, and operationalizing advanced analytics and machine learning solutions across the company's FinTech platforms. This role ...

Leverage expertise in data structures and algorithms to analyze and prepare data for modeling ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

Leverage expertise in data structures and algorithms to analyze and prepare data for modeling ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

... fintech, lending, or commercial credit * Proven understanding of credit underwriting principles, data science model application, risk appetite frameworks, and portfolio risk management. * Outstanding ...

$73K - $98K/yr

What We Do We are seeking a data-driven Marketing Analyst with 3-5 years of experience to support ... Experience in financial services , insurance, banking, lending, fintech, or other regulated ...

Senior Credit Risk Analyst

Atlanta, GA · On-site

$110 - $140/hr

... fintech, lending, or commercial credit * Proven understanding of credit underwriting principles, data science model application, risk appetite frameworks, and portfolio risk management. * Outstanding ...

... fintech, lending, or commercial credit * Proven understanding of credit underwriting principles, data science model application, risk appetite frameworks, and portfolio risk management. * Outstanding ...

This is a great opportunity for someone looking to build their career in fintech within a high ... Use available account data and payment behavior to prioritize follow-up and support effective ...

... supports analytics, reporting, and continuous improvement. The manager will lead a Power BI ... Automotive industry or FinTech experience PowerBI development experience .NET exposure 10+ years ...

It also requires a deep commitment to analyzing data, clearly articulating and presenting ... the fintech industry and our Risk Operations functional areas * Contribute to improvements in ...

It also requires a deep commitment to analyzing data, clearly articulating and presenting ... the fintech industry and our Risk Operations functional areas * Contribute to improvements in ...

Accounts Receivable Analyst II

Atlanta, GA · On-site

$23 - $29.25/hr

This is a great opportunity for someone looking to build their career in fintech within a high ... Use available account data and payment behavior to prioritize follow-up and support effective ...

This is a great opportunity for someone looking to build their career in fintech within a high ... Use available account data and payment behavior to prioritize follow-up and support effective ...

Showing results 21-40

Weekend Data Analyst Fintech information

What is the difference between Weekend Data Analyst Fintech vs Weekend Data Analyst Banking?

AspectWeekend Data Analyst FintechWeekend Data Analyst Banking
Required CredentialsBachelor's in Data Science, Finance, or related field; familiarity with fintech toolsBachelor's in Finance, Economics, or related; knowledge of banking systems
Work EnvironmentStartups, online platforms, flexible hoursTraditional bank branches, financial institutions, similar flexible weekend roles
Employer & Industry UsageFintech companies, online lenders, digital payment firmsCommercial banks, retail banking, financial services

The main difference between Weekend Data Analyst Fintech and Weekend Data Analyst Banking lies in the industry focus and work environment. Fintech roles are often in innovative, digital-focused companies requiring familiarity with new financial technologies, while banking roles are within traditional financial institutions emphasizing banking systems and regulations. Both roles typically require similar data analysis skills but cater to different sectors within finance.

What are the most commonly searched types of Data Analyst Fintech jobs in Georgia?

The most popular types of Data Analyst Fintech jobs in Georgia are:

What cities in Georgia are hiring for Weekend Data Analyst Fintech jobs?

Cities in Georgia with the most Weekend Data Analyst Fintech job openings:

Data Scientist

Worldpay, Inc.

Atlanta, GA • On-site

Full-time

Posted 11 days ago


Job description

Job Description

Are you curious, motivated, and forward-thinking? At FIS you'll have the opportunity to work on some of the most challenging and relevant issues in financial services and technology. Our talented people empower us, and we believe in being part of a team that is open, collaborative, entrepreneurial, passionate and above all fun.

About the role:

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory analysis as well as predictive models and AI solutions to solve business problems across the financial services industry, particularly in Risk, Fraud, Marketing, and Portfolio Management. Following the machine learning lifecycle, the data scientist should be able to convert the results into actionable product recommendations to present internally and externally.

What you'll be doing:

  • Participate in the design, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI solutions that drive measurable business outcomes.
  • Leverage expertise in data structures and algorithms to analyze and prepare data for modeling, assembling datasets from both standard and novel data sources and incorporate them into end-to-end analytical solutions.
  • Apply advanced machine learning, predictive analytics, natural language processing (NLP), and emerging AI techniques (GenAI, Agentic etc.) to solve complex business problems across the payments and financial services ecosystem.
  • Design and execute experiments, hypothesis testing frameworks, and statistical analyses to evaluate business strategies, product enhancements, and operational improvements.
  • Establish and promote best practices in data science, machine learning, feature engineering, experimentation, model governance, and MLOps throughout the organization.
  • Stay current on industry trends in machine learning, AI, Generative AI, and financial services analytics; bring relevant innovations to the team.

What you bring:

  • Master's degree or higher in Mathematics, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative discipline.
  • 1-3 years of experience developing and deploying end-to-end machine learning, predictive analytics, and data science solutions within the Payments, Banking, or Financial Services industry.
  • Strong proficiency in Python and SQL; experience with big data technologies such as Spark, PySpark, a plus.
  • Hands-on experience with data wrangling, feature engineering, and model development using libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, or Plotly.
  • Demonstrated experience building and deploying machine learning models in a production or near-production environment.
  • Proficiency with data visualization and business intelligence tools (e.g., Tableau or equivalent).
  • Strong analytical thinking and problem-solving skills; ability to translate ambiguous business problems into rigorous analytical frameworks.
  • Ability to work collaboratively across product, engineering, and business teams.

Nice to have:

  • Experience within the Payments, Banking, or Financial Services industry.
  • Hands-on experience with the Databricks platform, including MLflow, Model Registry, collaborative notebooks, and MLOps workflows.
  • Experience deploying cloud-native machine learning solutions, particularly within AWS environments.
  • Familiarity with emerging advancements in Transformer Models and Agentic AI technologies.
  • Knowledge of model governance, regulatory compliance, and MLOps best practices within regulated financial services environments.

What we offer you:

A career at FIS is more than just a job. It's the chance to shape the future of fintech. At FIS, we offer you:

  • A voice in the future of fintech
  • Always-on learning and development
  • Collaborative work environment
  • Opportunities to give back
  • Competitive salary and benefits


Privacy Statement

FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.

EEOC Statement

FIS is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here supplement document available here


For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.

Sourcing Model

Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.

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