Machine Learning Analyst | 100% Remoto | LATAM
What do we offer?
Prometeo Talent is a recruitment agency with a strong presence across the Americas and Europe.
We specialize in connecting companies with exceptional professionals across data, analytics, and business functions.
We have partnered with a U.S.-based company specialized in marketing effectiveness measurement.
They help organizations better understand consumer behavior, purchasing trends, brand performance, and market dynamics through data-driven insights.
We are looking for a Data Analyst (Machine Learning) to join our client's global team.
This role is ideal for analytical and data-driven professionals who enjoy working with large-scale consumer and retail datasets, bridging the gap between complex database structures and business strategy, and turning raw transactional or behavioral data into clear, actionable metrics.
The ideal candidate combines solid SQL and Python skills, a strong "numbers sense", attention to detail, and the ability to translate technical results into clear summaries for stakeholders in English.
The position is open to a range of experience levels, from recent graduates with a strong quantitative background to mid-level analysts looking to deepen their technical data manipulation skills.
About Us
Prometeo Talent is a recruitment agency with a strong presence across the Americas and Europe.
We specialize in connecting companies with exceptional professionals across data, analytics, and business functions.
We have partnered with a U.S.-based company specialized in marketing effectiveness measurement.
They help organizations better understand consumer behavior, purchasing trends, brand performance, and market dynamics through data-driven insights.
We are looking for a Data Analyst (Machine Learning) to join our client's general team.
This role is ideal for analytical and data-driven professionals who enjoy working with large-scale consumer and retail datasets, bridging the gap between complex database structures and business strategy, and turning raw transactional or behavioral data into clear, actionable metrics.
The ideal candidate combines solid SQL and Python skills, a strong "numbers sense", attention to detail, and the ability to translate technical results into clear summaries for stakeholders in English.
The position is open to a range of experience levels, from recent graduates with a strong quantitative background to mid-level analysts looking to deepen their technical data manipulation skills.
What You Will Do
Write, optimize, and execute SQL queries to extract data from relational databases and cloud data warehouses.
Develop, run, and validate machine learning, predictive,



or statistical matching models to uncover deeper consumer behaviors and forecast trends.
Slice, unpivot, and aggregate raw transactional or panel data to calculate core business metrics such as household penetration, market share, and purchasing trends.
Build and maintain clean, structured data tables and views that feed into recurring tracking reports and stakeholder dashboards.
Review query outputs, perform data audits, and double-check logic to ensure accuracy and data integrity before insights are finalized.
Use conditional logic and filtering techniques to segment data and isolate specific tracking cohorts.
Clean, parse, and cat production incident response, troubleshooting, mitigation, and root cause analysis.
Identify recurring operational issues and automate their resolution.
Implement AWS and Kubernetes security best practices.
Collaborate with Security teams to strengthen infrastructure security and support compliance initiatives.
Improve platform resilience, high availability, scalability, and disaster recovery capabilities.
Optimize AWS resource utilization and contribute to cloud cost optimization and FinOps initiatives.
Automate operating system and infrastructure configuration using Ansible or similar tools.
Develop operational tooling and automation using Python and Bash.
Collaborate with Engineering teams on platform architecture and deployment strategies.
Continuously evaluate new DevOps, cloud, Kubernetes, observability, and platform engineering technologies.
What You Bring
- 5–8+ years of experience working in DevOps, Platform Engineering, Site Reliability Engineering, Cloud Engineering, or similar roles.
Strong hands-on production experience with AWS.
Strong experience managing Kubernetes clusters, ideally Amazon EKS.
Advanced experience with Terraform and Infrastructure as Code.
Strong experience with Docker and containerized environments.
Hands-on experience building and maintaining CI/CD pipelines with:
GitHub Actions
Jenkins
GitLab CI
or similar platforms
Strong Linux administration skills.
Experience with configuration management tools such as Ansible.
Good scripting and automation capabilities with:
Python
Bash
Experience implementing observability using technologies such as:
Prometheus
Grafana
CloudWatch




OpenSearch / Elasticsearch
ELK
Strong understanding of networking concepts including:
VPCs
Subnets
Load Balancers
DNS
VPNs
Firewalls
Routing
Security Groups
Experience troubleshooting complex distributed systems and production environments.
Solid understanding of cloud security and infrastructure security best practices.
Experience supporting highly available, production-grade cloud environments.
Strong communication skills and ability to collaborate with engineering, security, QA, and business stakeholders.
High degree of autonomy, ownership, and analytical problem-solving ability.
Bachelor's degree in Computer Science, Software Engineering, Systems Engineering, or a related technical discipline, or equivalent professional experience.
Core Technology Stack
You'll work with technologies including:
AWS
Kubernetes / EKS
Docker
Terraform
Ansible
GitHub Actions
Jenkins
Linux
Python
Bash
Prometheus
Grafana
CloudWatch
OpenSearch / Elasticsearch
Nice to Have
Experience with HashiCorp Nomad.
Experience with HashiCorp Consul.
Broader experience with the HashiCorp ecosystem.
Experience operating Kafka in production.
Experience supporting data infrastructure based on:
ClickHouse
Elasticsearch
MongoDB
Redis
Experience with distributed systems and high-volume data platforms.
Previous experience in cybersecurity, identity security, or security SaaS platforms.
Experience working with cloud security controls and compliance frameworks.
Experience with FinOps and cloud cost optimization.
Experience designing internal developer platforms or platform engineering capabilities.
Exposure to infrastructure supporting AI/ML or LLM-based applications.
What Success Looks Like
Success in this role means:
Increasing infrastructure reliability and availability.
Reducing deployment friction and improving engineering velocity.
Increasing infrastructure automation and reducing manual operational work.
Improving observability and reducing mean time to detection and resolution.
Operating Kubernetes workloads reliably at scale.
Strengthening security throughout cloud infrastructure and deployment processes.
Improving AWS cost efficiency without compromising reliability.
Contributing reusable platform capabilities that allow engineering teams to move faster.
Continuously improving production readiness as the platform scales.
What Darwoft Offers
Contractor agreement with payment in USD
100% remote work
Argentina's public holidays
English classes
Referral program
Access to learning platforms
Explore this and other opportunities at:
#J-*****-Ljbffr

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