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Remote Data Science Jobs in Decatur, GA (NOW HIRING)

Location- Hybrid (3 days in office, 2 days remote): Atlanta, GA, Columbus, GA or Jacksonville, FL ... Establish and promote best practices in data science, machine learning, experimentation, model ...

Senior Data Scientist

Atlanta, GA · On-site +1

$146K - $304K/yr

  • Medical

  • Retirement

Lead the design and development of advanced data science and machine learning analytics models using structured, unstructured and semi-structured data. * Work with engineers to design and implement ...

Principal Data Scientist - CX Analytics

Atlanta, GA · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

In this role, you will drive applied data science work that goes beyond modeling-mining structured ... Current remote and field-based Unum employees may apply and will be considered in accordance with ...

Data Scientist II - CX Analytics

Atlanta, GA · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

In this role, you will focus on executing applied data science work-running analyses, supporting ... Current remote and field-based Unum employees may apply and will be considered in accordance with ...

... and remote resources to get the job done - consistently Here is the Job details: Title: Data ... Masters in mathematics, statistics or computer science or related field - Ph D. degree preferred 5 ...

Lead Data Engineer 2026- US

Atlanta, GA · On-site +1

$110K - $132K/yr

Aimpoint Digital is a dynamic and fully remote AI and Data consultancy. We work alongside the most ... Collaborate with analytics, data science, and ML project teams to productionize AI-enabled ...

Lead Machine Learning Engineer - REMOTE

Atlanta, GA · Remote

$98K - $129K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

This is a key role on the Applied AI & Data Science team, sitting at the intersection of software ... Remote work schedule, with a preference for candidates based in Miami, FL; Bentonville, AR; or ...

Data Engineer - GCP

Atlanta, GA · Remote

$117K - $140K/yr

  • Medical

  • Dental

  • Vision

Work closely with data scientists and analysts to understand data needs and business goals ... Flexible work environment and remote work options. Join us and be part of a team building ...

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

  • Medical

  • Dental

  • Vision

Work closely with data scientists and analysts to understand data needs and business goals ... Flexible work environment and remote work options. Join us and be part of a team building ...

Showing results 21-40

Remote Data Science information

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

What are the qualifications to get a remote data science job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

What are the key skills and qualifications needed to thrive as a remote data scientist, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is the difference between Remote Data Science vs Remote Data Analyst?

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

Can I work remotely as a data scientist?

Yes, many data scientist roles are available as remote positions, especially in companies that prioritize flexible work arrangements. Remote data scientists typically need strong skills in programming, data analysis, and tools like Python or R, and may require familiarity with cloud platforms and collaboration tools. Availability depends on the employer's policies and the specific job requirements.

What are the most commonly searched types of Data Science jobs in Decatur, GA?

The most popular types of Data Science jobs in Decatur, GA are:

What are popular job titles related to Remote Data Science jobs in Decatur, GA?

For Remote Data Science jobs in Decatur, GA, the most frequently searched job titles are:

What job categories do people searching Remote Data Science jobs in Decatur, GA look for?

The top searched job categories for Remote Data Science jobs in Decatur, GA are:

What cities near Decatur, GA are hiring for Remote Data Science jobs?

Cities near Decatur, GA with the most Remote Data Science job openings:

Infographic showing various Remote Data Science job openings in Decatur, GA as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Data Scientist Sr Lead

Worldpay, Inc.

Atlanta, GA • On-site, Remote

Full-time

Re-posted 11 days ago


Job description

Job Description

At this time, we are unable to offer visa sponsorship for this position. Candidates must be legally authorized to work for any employer in the United States (or applicable country) on a full-time basis without the need for current or future immigration sponsorship.

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 Team

FIS-Total Issuing Solutions one of the leading credit card processors globally. You will help build production level machine learning models that enhance the value and efficiency of this financial system. As a member of the Data & Analytics team, the data scientist will deploy data-driven exploratory analysis as well as predictive models to solve business problems across the financial services industry, particularly in thearea of 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. They will lead Analytics Model development, validation, monitoring, and visualization.

Location- Hybrid (3 days in office, 2 days remote): Atlanta, GA, Columbus, GA or Jacksonville, FL


What you will be doing

  • Lead the design, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI solutions that drive measurable business outcomes.

  • Design and execute experiments, hypothesis testing frameworks, and statistical analyses to evaluate business strategies, product enhancements, and operational improvements.

  • Analyze and mine large-scale structured and unstructured datasets to uncover actionable insights, identify emerging trends, and support strategic decision-making.

  • Develop, test, and operationalize analytical and machine learning solutions for both internal stakeholders and external clients, ensuring scalability, reliability, and business impact.

  • Apply advanced machine learning, predictive analytics, natural language processing (NLP), and emerging AI techniques to solve complex business problems across the payments and financial services ecosystem.

  • Lead independent quantitative research initiatives, leveraging multiple data sources to generate innovative insights and identify new business opportunities.

  • Partner with product, engineering, business, and executive stakeholders to translate business objectives into data-driven solutions and measurable outcomes.

  • Communicate complex analytical findings through compelling storytelling, executive-ready presentations, dashboards, and visualizations that drive informed decision-making.

  • Design and develop automated dashboards, performance scorecards, and self-service analytics solutions to monitor key business metrics, customer behaviors, model performance, and operational health.

  • Establish and promote best practices in data science, machine learning, experimentation, model governance, and MLOps throughout the organization.

  • Lead proof-of-concept (POC) initiatives to evaluate emerging technologies, machine learning techniques, and Generative AI capabilities, translating successful pilots into production-ready solutions.

  • Drive model lifecycle management, including feature engineering, model training, validation, deployment, monitoring, retraining, and performance optimization.

  • Mentor and develop junior data scientists, fostering a culture of technical excellence, innovation, collaboration, and continuous learning.

  • Provide technical leadership and guidance on analytical methodologies, model selection, data quality, and solution architecture.

  • Collaborate with data engineering teams to define data requirements, optimize data pipelines, and ensure availability of high-quality data for analytics and machine learning initiatives.

  • Ensure adherence to regulatory, security, compliance, and model governance standards within a highly regulated financial services environment.

  • Stay current on industry trends and advancements in machine learning, artificial intelligence, Generative AI, cloud technologies, and financial services analytics.

  • Contribute tostrategic planning by identifying opportunities where advanced analytics and AI can create competitive advantage and business value.

  • Perform other duties and responsibilities as assigned.

Job Specific Skills/Leadership

  • Mentor and coachjunior data scientists, fostering a culture of continuous learning and technical excellence.

  • Provide constructive feedbackthrough regular code reviews and design critiques to elevate the team's engineering and modeling standards.

  • Identify skill gapswithin the team and develop training initiatives to build core competencies in advanced machine learning and data engineering.

  • Own the end-to-end deliveryof complex predictive and prescriptive analytics initiatives, from initial scoping to operational handover and monitoring.

  • Translate ambiguous business problemsinto rigorous analytical frameworks, setting clear project milestones and success criteria.

  • Drive innovationby researching new algorithms, tools, and methodologies that can improve the company's data infrastructure and capabilities.

  • Partner with product, engineering, and business stakeholdersto align data science initiatives with broader organizational goals and product roadmaps.


What you will bring

Minimum Qualifications

  • Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or another quantitative discipline.

  • 5+ 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 data science programming languages and big data technologies, including Python, SQL, Spark, PySpark, R, and Hadoop.

  • Extensive experience with data wrangling, feature engineering, and model development using libraries such as Pandas, NumPy, Scikit-learn, Plotly, Matplotlib, and Seaborn.

  • Advanced expertise in data visualization and business intelligence platforms, including Tableau.

  • Hands-on experience with the Databricks platform, including MLflow, AutoML, Model Registry, collaborative notebooks, and MLOps workflows.

  • Demonstrated ability to identify innovative business opportunities, develop proof-of-concepts (POCs), and translate successful pilots into scalable solutions.

  • Strong experience building and deploying machine learning models, including classification, clustering, and predictive models such as Random Forest, XGBoost, Gradient Boosting, and K-Means.

  • Experience applying Natural Language Processing (NLP) techniques to solve business challenges.

  • Proven ability to communicate complex analytical concepts and insights to both technical and non-technical stakeholders.

Preferred Qualifications

  • Ph.D. in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.

  • Experience designing and deploying cloud-native data science and machine learning solutions within AWS environments.

  • Demonstrated success in productizing machine learning models and analytics solutions for enterprise-scale production environments.

  • Experience leading the deployment, monitoring, governance, and lifecycle management of production-grade machine learning applications.

  • Knowledge of Generative AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and related frameworks.

  • Experience mentoring junior data scientists and providing technical leadership across complex analytics initiatives.

  • Familiarity with modern MLOps practices and model governance within regulated financial services environments.

What we offer you:

A career at FIS is more than just a job. It's the change 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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