Careers at Analytics 4 Retail
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Join a team that’s reshaping data in retail — one solution at a time.
Why Work With Us?
- Remote-First: Work from anywhere in LATAM — or beyond.
- Top-Tier Clients: Build real products with real impact for U.S. retailers.
- Career Growth: Access to training, mentorship, and leadership tracks.
- Strong Culture: Outcome-focused, respectful, and collaborative.
- Fair Pay: Competitive compensation in USD, paid reliably and transparently.
Imagine Your Dream Work Environment
Culture
- In Analytics 4 Retail we encourage a culture of mutual trust, where everyone has access to everything. Nobody will micro-manage you, because we know that every member shares the company's values and vision.
- We care about our members, that's why we provide amazing benefits and career paths. Everyone's always available if someone needs help; we are a big family that wishes to grow together and be successful as a whole.
What We Value
- If you are part of the Analytics 4 Retail family, you are passionate about data and technology, you love what you do but also like being challenged and learning new things constantly, that's why we are completely flexible with our members.
- Also, we love people that know how to fail, we are a humble company that appreciates someone that knows how to rise up stronger when being down, and also that keeps improving themselves and helps others do the same!
Apply for the role you are more passionate about
We always have these positions open. Seniority, specific clients and technologies come in later. We just want to know who wants to work as what. Don’t worry too much about your past experience, find the best fit for your future goals
Data Engineering
Design, build, and optimize data pipelines and infrastructure using tools like Airflow, Spark, dbt, and Snowflake.
Data Science
Develop predictive models, customer segmentation, and optimization solutions using advanced ML techniques.
Data Analysis
Translate complex data into actionable insights for our retail clients, building reports, dashboards, and KPIs.
Business Intelligence
Work with stakeholders to build dashboards and reporting systems that drive strategic decisions.
Artifical Intelligence
Build AI-powered tools, agents, and assistants for internal and external clients. Deploy models to the cloud seamlessly.
Machine Learning
Productionize ML models and build scalable pipelines to support data science applications.
Cloud
Manages and optimizes infrastructure, services, and applications hosted on cloud platforms like AWS, GCP, or Azure.
Quality Assurance
Ensure quality across data pipelines, dashboards, and deployments with both manual and automated testing.
DevOps
Focuses on automating and streamlining the software development and deployment process.
Security
Protects systems, data, and networks from breaches, attacks, and unauthorized access.
Product Owner
Defines product vision and priorities, translating business needs into features for development teams.
Project Management
Manage project delivery across cross-functional data teams, ensuring milestones and client satisfaction.