Data Scientist Growth Intelligence & RevOps

What is Cobre, and what do we do?

Cobre is Latin America’s leading instant b2b payments platform. We solve the region’s most complex money movement challenges by building advanced financial infrastructure that enables companies to move money faster, safer, and more efficiently.

We enable instant business payments—local or international, direct or via API—all from a single platform.

Built for fintechs, PSPs, banks, and finance teams that demand speed, control, and efficiency. From real-time payments to automated treasury, we turn complex financial processes into simple experiences.

Cobre is the first platform in Colombia to enable companies to pay both banked and unbanked beneficiaries within the same payment cycle and through a single interface.

We are building the enterprise payments infrastructure of Latin America!

What we are looking for:

Join Cobre as a RevOps Data Science Systems Engineer, where you'll build data and AI infrastructure to support revenue operations and growth intelligence. This role focuses on growing revenue by providing intelligence backed by AI and advanced analytics that optimize customer lifecycle management across our platform.

You'll create predictive analytics solutions, implement AI-powered automation within RevOps workflows, and democratize data science capabilities across revenue-generating teams. We're seeking a data scientist with strong data engineering skills who can translate business challenges into intelligent, automated solutions that drive measurable revenue growth.

What would you be doing:

• AI-Powered Systems Development: Develop and deploy machine learning models for lead scoring, churn prediction, expansion opportunities, and revenue forecasting. Integrate AI solutions into CRM workflows using frameworks like N8N and modern ML libraries, creating automated decision-making systems that optimize customer lifecycle management.
• Intelligent Automation & Analytics: Build AI-powered dashboards and alerting systems using tools like Streamlit that democratize advanced analytics across sales, marketing, and customer success teams. Implement explainable AI solutions and statistical analysis to provide transparent insights for business stakeholders.
• Data Engineering for Revenue Intelligence: Build robust data pipelines (dbt, Airflow, Snowflake) that unify customer data across CRM platforms (Salesforce, HubSpot), billing systems, and marketing automation tools. Design scalable data architectures that support real-time analytics and machine learning model serving for revenue operations.
• Data Infrastructure & Model Operations: Design and maintain APIs for model serving, implement MLOps practices for continuous model improvement, and ensure seamless integration between data systems and AI applications. Create data products that enable self-service analytics while maintaining governance standards.
• Cross-Functional Data Solutions: Partner with Sales Operations, Marketing Operations, Customer Success, and Finance teams to understand data requirements and deliver AI-enhanced workflow solutions. Translate business challenges into data engineering and machine learning problems with measurable impact.

What do you need:

Experience & Education:

• 2-5 years in data engineering, data science, or systems engineering roles
• Bachelor's degree in Computer Science, Data Engineering, Mathematics, Statistics, or related technical field
• Experience building and deploying data pipelines and analytics solutions in production environments

Technical Skills:

• Data Engineering: Strong proficiency in SQL, Python, and modern data stack technologies (dbt, Airflow, Snowflake/Redshift/Databricks). Experience with cloud platforms (AWS/GCP) and API development.
• Machine Learning & AI: Hands-on experience with ML libraries (scikit-learn, pandas), AI frameworks (LangChain, LangGraph), and model deployment practices. Understanding of statistical analysis and A/B testing methodologies.
• RevOps Platforms: Experience with CRM systems (Salesforce, HubSpot), including custom objects, workflows, and API integrations. Knowledge of billing systems and marketing automation tools.
• Analytics & Visualization: Proficiency with BI tools (Sigma, Tableau) and application development frameworks (Streamlit) for creating data products.

Business & Communication:

• Understanding of revenue operations processes, customer lifecycle management, and subscription business metrics
• Strong communication skills with ability to translate technical solutions for business stakeholders
• Experience collaborating with sales, marketing, and customer success teams
• Bilingual in English and Spanish is highly desirable

Nice to Have:

• SaaS/FinTech experience with focus on growth analytics and revenue operations
• Experience with MLOps tools, customer data platforms (CDPs), and advanced analytics techniques
• Salesforce or HubSpot certifications
• Knowledge of time series forecasting, cohort analysis, and attribution modeling

Join us at Cobre, where your data science expertise and AI implementation skills will power the next generation of intelligent revenue operations across Latin America.