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Remote Retail Data Systems Jobs (NOW HIRING)

Appriss Retail

Data Science Manager

$160K - $170K/yr

About Appriss Retail Appriss Retail is the total retail loss solution for omnichannel, unifying ... The right candidate has built and shipped real data platforms and AI/ML systems using a modern ...

Crisp, Inc.

Enterprise Sales Director - Retail

As the leading AI vertical retail data company, Crisp leverages AI to facilitate the integration ... Work both independently and collaboratively in a fast-paced, remote environment. * Deliver ...

New

Link Up Overseas

Remote Entry-Level Data Entry Specialist

$17.50 - $23.25/hr

Accurately input and update data into our databases and systems. * Verify and correct data ... Flexible remote work environment - work from the comfort of your home or any location that suits ...

Apex Informatics

Data Engineer

$117K - $140K/yr

Remote Duration: 06 Months (C2H Role) Main Skills: Data Engineer/ Python/Pyspark/ SQL/ ETL/ DBT ... Kafka, Tableau • Strong understanding of healthcare data systems and experience leading data ...

Innowhyte Inc

Optimize and manage data storage systems and ensure high availability, reliability, and performance. Design, develop, and maintain robust and scalable ETL (Extract, Transform, Load) and ELT (Extract ...

Apex Informatics

DATA ENGINEER

$117K - $140K/yr

Remote Duration: 06 Months (C2H Role) Main Skills: Data Engineer/ Python/Pyspark/ SQL/ ETL/ DBT ... Strong understanding of healthcare data systems and experience leading data engineering teams

Innowhyte Inc

... data systems. If you have a passion for working with data and enabling AI/ML capabilities in products, we want to hear from you. Key Responsibilities: • Design, develop, and maintain robust and ...

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Remote Retail Data Systems information

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$10

$49

$74

How much do remote retail data systems jobs pay per hour?

As of Aug 29, 2026, the average hourly pay for remote retail data systems in the United States is $49.16, according to ZipRecruiter salary data. Most workers in this role earn between $38.46 and $59.13 per hour, depending on experience, location, and employer.

What is the difference between Remote Retail Data Systems vs Remote Retail Data Analysts?

AspectRemote Retail Data SystemsRemote Retail Data Analysts
CredentialsTypically requires knowledge of data management, retail systems, and sometimes certifications in data or retail softwareRequires analytical skills, proficiency in data analysis tools, and often a degree in data science, statistics, or related fields
Work EnvironmentFocuses on managing retail data systems, software configuration, and data integrity remotelyInvolves analyzing retail data, generating reports, and providing insights remotely
Industry UsageUsed by retail companies to maintain and optimize data systemsEmployed by retail firms to interpret data and support decision-making

Remote Retail Data Systems professionals focus on managing and maintaining retail data infrastructure, while Remote Retail Data Analysts interpret data to inform business strategies. Both roles are essential in retail data management but differ in their primary functions and skill sets.

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Cities with the most Remote Retail Data Systems job openings:

What are the most commonly searched types of Retail Data Systems jobs?

The most popular types of Retail Data Systems jobs are:

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Remote Retail Data Systems jobs near you
Infographic showing various Remote Retail Data Systems job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, 9% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $102,260 per year, or $49.2 per hour.

Data Science Manager

Appriss Retail

Remote

$160K - $170K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 20 days ago

Job description

About Appriss Retail
Appriss Retail is the total retail loss solution for omnichannel, unifying high-quality data across stores, online, and customer ser-vice to reduce returns, cut shrink, and manage incidents. Our products-Engage to reduce returns, Secure to cut shrink, and Incident to centralize visibility-help retailers move from reactive loss control to strategic profit protection. Together, they empower organizations to make better operations decisions, strengthen accountability, and put hundreds of millions back to the bottom line. Covering 40% of all U.S. transactions and active in 45 countries, Appriss Retail is trusted by 60+ of the top 100 U.S. retailers to deliver lasting performance improvement. Learn more at apprissretail.com.
Overview
The Data Science Manager is a player-coach who leads a small, high-output team while staying deeply hands-on. This role owns the full scope of data science at Appriss Retail - data engineering, governance, and production model delivery - not just model building. The right candidate has built and shipped real data platforms and AI/ML systems using a modern stack, has meaningful experience with LLMs and agentic architectures, and can operate credibly in both the technical weeds and the business conversation.
This is not a role for someone who manages from a distance. You will write code, review pipelines, define data contracts, and drive architectural decisions - while also growing and directing the team around you.
Essential Duties
Technical leadership & delivery
  • Own end-to-end delivery of high-impact data science projects - from ambiguous business request to production-ready system.
  • Design and maintain data pipelines, data models, and governance standards alongside your team; treat infrastructure as a first-class product concern.
  • Build, evaluate, and iterate on ML models in production; lead experimentation rigor, monitoring, and lifecycle management.
  • Architect and ship LLM-integrated features and agentic workflows - including prompt engineering, tool use, and output evaluation.
  • Guide cloud infrastructure architecture for data science projects, taking into account performance, maintenance, and cost criteria.
  • Set the standard for code quality: write production-grade Python and SQL, enforce review practices, and maintain documentation.
  • Partner closely with engineering to integrate models and pipelines into core product infrastructure.

People & team
  • Directly manage 2-4 data scientists; provide technical mentorship, career development, and clear performance expectations.
  • Define team operating norms: sprint planning, code review, documentation, and delivery accountability.
  • Recruit and grow the team as the function scales.

Strategy & stakeholders
  • Translate ambiguous business problems into well-scoped analytical and modeling work with defined success criteria.
  • Partner with product, engineering, and business stakeholders to ensure data work is grounded in real source systems and product context - not isolated analysis.
  • Contribute to the data and analytics roadmap, balancing near-term delivery with longer-term platform investment.
  • Communicate clearly to non-technical audiences; influence decisions with data and model outputs.

Required Qualifications
Education & Experience
  • Master's degree in a quantitative field, or bachelor's with significant professional experience.
  • 6+ years of experience in data science, data engineering, or a closely related technical discipline.
  • 1+ year of direct people management or formal technical lead experience over a team.

Technical skills - required
  • Expert-level SQL and Python; production code, not just analysis scripts.
  • Deep understanding of data infrastructure: pipelines, warehousing, data modeling, and source system behavior.
  • Hands-on ML experience: model training, evaluation, deployment, monitoring, and iteration.
  • Strong software engineering practices: version control, code review, testing, and CI/CD familiarity.
  • Ability to scope and deliver complex analytical projects independently from vague inputs.
  • Cloud data platform experience: Snowflake, Azure (preferred), AWS, or GCP.

Preferred Qualifications
  • Proficiency with modern data stack tooling: dbt, Airflow, Spark, or equivalent.
  • Demonstrated LLM experience: prompt engineering, RAG, fine-tuning, or agent frameworks (LangChain, LlamaIndex, or equivalent)
  • Experience and familiarity with agentic AI architectures: multi-step reasoning, tool use, memory, and orchestration.
  • Experience in retail, fraud detection, or transaction-level data at scale.
  • Familiarity with ML platform tooling: MLflow, feature stores, model registries, or similar.

Benefits
At Appriss Retail, we offer a competitive and comprehensive benefits package designed to support your well-being at work and beyond. Benefits begin on your first day and include multiple medical plan options, dental and vision coverage, health savings and flexible spending accounts, paid parental leave, and supplemental coverage for life's unexpected moments. We offer generous paid time off, a 401(k) with immediate vesting and company match, short- and long-term disability, and free access to health and wellbeing resources such as Calm and Sworkit. You'll also have access to learning and development opportunities to help you grow your career. Our benefits support your well-being so you can perform your best in every part of life.
Reports to: Director of Data Science
Department: Data Science
Supervisory Duties: Yes
Travel Required: Minimal (optional)
Location/Work Region: Remote - United States
This job is eligible for a 12-15% bonus in addition to the base salary.
We are proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to protected characteristics.
The pay range for this role is:
160,000 - 170,000 USD per year (Remote (United States))

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