Remote opportunity at
DaCodesSenior Data Scientist con IA Aplicada- LATAM Only
This is a remote, LATAM-only senior role focused on applied data science and artificial intelligence. The position is with DaCodes, a software and digital transformation firm…
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About This Role
This is a remote, LATAM-only senior role focused on applied data science and artificial intelligence. The position is with DaCodes, a software and digital transformation firm with close to 300 team members that works on projects for clients in Latin America and the United States. The hire would be placed on a client project with a fintech startup. The client moves money between the United States, Mexico and Central America.…
Job Description
This is a remote, LATAM-only senior role focused on applied data science and artificial intelligence. The position is with DaCodes, a software and digital transformation firm with close to 300 team members that works on projects for clients in Latin America and the United States. The hire would be placed on a client project with a fintech startup.
The client moves money between the United States, Mexico and Central America. Its product is a conversational assistant that guides users from getting a quote through to payment, and it is moving from a chatbot toward a conversational agent. The data team is small and maintains the data warehouse and an MCP server connected to the company's corporate AI platform. The team is now expanding into predictive models, including an in-house fraud scoring model that must work across several countries, user segmentation, and agents that turn model output into actionable insights.
The person in this role would build models, evaluate them rigorously and bring them into production alongside LLM-based agents. The work spans exploratory analysis of transactional, conversational and contextual data, defining product and funnel metrics, and building dashboards for non-technical teams. The posting favors someone who can move quickly in a startup setting where priorities shift and workloads peak, and who will share good practices with the team.
Applicants need at least four years in data science or machine learning, including one year building LLM solutions that reached production, and at least one predictive model in production with a clear business effect. Candidates must live in a Latin American country, be comfortable working remotely with distributed teams, and be available during hours that overlap with Mexico City. English should be intermediate to advanced in speech and writing.
Responsibilities
- Design, train and deploy predictive models such as fraud scoring, user segmentation and behavior models, and measure their business value.
- Build and evolve conversational agents and LLM workflows using RAG, tool calling and MCP that turn model results into actionable insights.
- Evaluate models and agents with metrics, traces and continuous testing, and optimize cost and latency in production.
- Run exploratory analysis on transactional, conversational and contextual data and turn findings into business decisions.
- Work with engineering and data teams to widen the data sources available through the MCP server and protect data quality and integrity.
- Define and adjust product and funnel metrics when hypotheses change, and identify missing data needed to pivot quickly.
- Present results in dashboards and BI tools so non-technical teams can make data-informed decisions.
- Document and share data science and applied AI practices with the team.
Requirements
- 4 or more years in data science or machine learning, with at least one year building LLM solutions that reached production.
- At least one predictive model taken into production, with the ability to explain its impact on the business.
- Core Python for data science and ML (pandas, scikit-learn) and advanced SQL on a data warehouse.
- Predictive modeling in production, including regression, classification and segmentation, with validation and monitoring.
- LLMs and agents in production, including RAG, tool calling and orchestration with LangChain, LangGraph or similar.
- Model and LLM evaluation and tracking, such as MLflow, traces and quality metrics.
- Experience working remotely with distributed teams.
- Ability to explain technical results to non-technical audiences and to manage several workstreams when priorities change.
- Residence in a Latin American country, intermediate to advanced English in speech and writing, and availability close to Mexico City working hours.
Qualifications
- XGBoost or LightGBM experience.
- Experience creating MCP servers or connecting agents to internal data.
- Semantic caching and methods to reduce inference cost and latency.
- BI experience with Looker, Metabase, Power BI or Tableau.
- AWS or GCP and FastAPI for serving models and services.
- Experience with fraud detection, risk or scoring.
- Degree in computer science, mathematics, statistics or a related field.
- Personal projects, publications, open-source contributions, or ML and cloud certifications.
Core Skills
Benefits
- Remote work with a home office setup.
- Schedule set to the team or project, Monday to Friday.
- A day off on your birthday.
- Major medical insurance and life insurance (applies in Mexico).
- Multicultural teams and virtual integration events.
- Access to courses, certifications and English classes.
- Opportunities across the company's different business lines.
- Company certified as a Great Place to Work.
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where can I work from?
The role is remote and open only to candidates who live in a Latin American country. Availability close to Mexico City working hours is also expected.
What are the core technical requirements?
The posting asks for Python for data science and machine learning, advanced SQL, production predictive modeling, and LLM agents using RAG and tool calling.
How much experience is needed?
At least four years in data science or machine learning, including one year building LLM solutions that reached production.
Is a salary stated?
The posting does not specify a salary.
What is the employment type?
The posting describes a full-time position.
Sample Interview Questions
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