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Remote Data Science Jobs in Georgia (NOW HIRING)

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QA Analyst - Trading Data & Pricing

Atlanta, GA · On-site +1

$85K - $115K/yr

Collaborate closely with Product, Engineering, Data Science, and Game Operations teams to support ... S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks: The typical ...

New

One Ten Inc

Software Roles

Atlanta, GA · Remote

$117K - $155K/yr

... * Sr. Data Scientist * Sr. AI Engineer * Sr. Data Engineer Job Locations: Remote (US) Sr/Staff Infrastructure Software Engineer: Required Skills: * 6+ years with Go, Python, Java or similar ...

SynergisticIT

AI / ML Engineer

Atlanta, GA · On-site +1

With remote work and global talent pools, even entry-level roles receive hundreds of applications ... Data Scientists & Machine Learning Engineers * Data Engineers * Required & Preferred Skills * Java ...

Deckers

United States (Remote) Interested applicants must reside in one of the following approved states ... Bachelor's degree required, preferably in Computer Science, Engineering, or related technical field;

kgs

Data Analyst I

Atlanta, GA · On-site +1

Bachelor's degree in Statistics, Mathematics, Economics, Data Science, or a related field from an accredited college or university * A minimum of 3 years of relevant post-baccalaureate professional ...

Booz Allen Hamilton

Data Management Analyst

Atlanta, GA · On-site +1

As part of our team, you'll work with world-class scientists, technical experts, and public health ... Experience supporting or developing programs involving digital health technologies, such as remote ...

Deloitte

GCP Manager

Atlanta, GA · On-site +1

Support existing data science and modeling teams by aligning platform capabilities to business and ... remote client service delivery. Recruiting for this role ends on 06/30/2026. Work you'll do As a ...

Sortly

Senior Product Manager

Atlanta, GA · Remote

$121K - $160K/yr

We are proudly a distributed and remote-first company since inception with teams across 4 countries ... You'll work closely with engineering, design, and data science teams to deliver intelligent product ...

CSAA

... Data Science, Technology, Actuarial, Legal, and Compliance - the Product Manager III envisions ... We embrace a remote-first culture through our Flexible Workplace. Most employees hold Home-Flex ...

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Remote Data Science information

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 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.

Can a data scientist work fully remote?

Yes, many data scientists work fully remote, especially in companies that prioritize flexible work arrangements. Remote data science roles often require strong communication skills, proficiency with collaboration tools, and the ability to work independently on projects using programming languages like Python or R. However, some positions may require occasional in-person meetings or on-site presence depending on company policies.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Will AI replace data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not eliminate the need for human expertise in interpreting results, designing models, and making strategic decisions. Data scientists will continue to be essential for developing complex algorithms, understanding business context, and ensuring ethical use of AI tools. Skills in programming, statistical analysis, and machine learning remain critical for the profession's evolving landscape.

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 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.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables, optimize models, and prioritize tasks for efficiency.
More about Remote Data Science jobs
What are the most commonly searched types of Data Science jobs in Georgia? The most popular types of Data Science jobs in Georgia are:
What are popular job titles related to Remote Data Science jobs in Georgia? For Remote Data Science jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Remote Data Science jobs in Georgia look for? The top searched job categories for Remote Data Science jobs in Georgia are:
What cities in Georgia are hiring for Remote Data Science jobs? Cities in Georgia with the most Remote Data Science job openings:
Remote Data Science jobs near you
Infographic showing various Remote Data Science job openings in Georgia as of June 2026, with employment types broken down into 2% As Needed, 72% Full Time, 21% Part Time, and 5% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.
Senior Payments Data Optimization Analyst

Senior Payments Data Optimization Analyst

Optimized Payments

Atlanta, GA • On-site, Remote

$82K - $104K/yr

Other

Posted 5 days ago

Job description

Who are you?

Are you a strategic mastermind and part organizational guru looking to join a fintech? Look no further! Optimized Payments is seeking a highly motivated and experienced Senior Payments Data Optimization Analyst to join our growing team.

OP is seeking an innovative and dedicated individual committed to both serving our customers and having fun! Driven, with an entrepreneurial spirit and a heart for fintech. We're looking for someone who wants to make a significant impact on the Company, Clients, and your Career. At Optimized Payments, our people embrace these qualities, so if this sounds like you then please read on!

The Role:

The Senior Payments Data Optimization Analyst serves as the technical business liaison between Optimized Payments' consulting team and internal Data Engineering and Data Science partners. The role focuses on transaction-level data, aggregated data, reporting accuracy, and performance optimization across our client base.

Approximately 75% of the role partners with technical teams on data quality, analytics, and optimization initiatives, with 25% supporting client-facing insights and consulting discussions across platforms such as Fiserv, Chase, Stripe, Adyen, Worldpay, etc.

While this is a hybrid position based in Atlanta, you will have the opportunity to work remote primarily.

Responsibilities:

Data Quality, Normalization & Governance

  • Identify, track, and escalate data discrepancies or integrity issues impacting analytics, KPIs, client reporting, and analysis.
  • Support data normalization efforts of authorization, clearing, settlement, and fee data across multiple processors, gateways, and client data sources.
  • Partner with data engineering teams to define data requirements, schemas, and transformation logic for payment analytics requirements and improve data pipelines.
  • Contribute to and maintain documentation of data definitions, KPI logic, and calculation methodologies.
  • Assist in maintaining consistent reporting standards and governance controls across clients.
  • Validate reporting outputs and ensure alignment between source transaction data and downstream dashboards.
  • Review source-to-target mappings, schemas, and transformations to ensure accuracy of downstream reporting.

Payments Performance & Optimization

  • Analyze transaction, authorization, decline, fee, and network data to identify optimization opportunities for existing clients.
  • Monitor and report on key payments KPIs (e.g., authorization rates, interchange impact, routing performance, fraud indicators).
  • Develop data-driven recommendations to improve payments performance and reduce cost for our clients.
  • Support testing and performance initiatives for clients (e.g., routing strategies, retry logic, tokenization adoption, configuration changes).
  • Quantify impact of optimization initiatives and track performance over time.

Client Support & Insights

  • Prepare client-facing reporting and performance summaries using our proprietary analytics platform.
  • Translate complex payment and operational data into clear, actionable recommendations.
  • Support consulting discussions with analytical context, benchmarking, and scenario modeling.

Cross-Functional Collaboration

  • Partner with Technology, Data Engineering, Product, and Client teams to implement and measure optimization initiatives.
  • Help define business requirements for reporting enhancements and data improvements.
  • Document findings, assumptions, and measurable outcomes of optimization efforts.

Skills and Qualifications:

  • Bachelor's degree in a related field such as Finance, Statistics, Economics, or Computer Science.
  • 3-5 years of experience in payments, analytics, finance, consulting, or related field.
  • Experience with card payments, interchange, authorization strategies, or network data is required.
  • Strong analytical skills and experience working with large datasets.
  • Proficiency in SQL and experience with BI tools (e.g., Tableau, Power BI, Looker).
  • Ability to communicate insights clearly to both technical and non-technical stakeholders.
  • Strong attention to detail and structured problem-solving approach.
  • Knowledge of credit card scheme regulations, disputes, and chargeback processes.
  • Familiarity with payment gateways, processors, or fraud tools, including cross-border and local payment methods.
  • Deep understanding of how these systems interconnect and the resulting impact on credit card payment success.
  • Understanding of A/B testing or performance experimentation frameworks.

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