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Senior Data Science Analyst – CRM
Banco Mercantil. Develop, validate, and deploy product propensity, churn, LTV, recommendation, clustering, and anomaly detection models .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and deploying machine learning models, including propensity, churn, and anomaly detection, while ensuring scalability and governance of workflows. Proficient in translating complex technical concepts into actionable insights for leadership and fostering a data-driven culture within teams.
Highest-signal resume keywords
Machine Learning Model DevelopmentPython or R ProficiencySQL ProficiencyData Visualization Tools (Power BI, Tableau, Looker)Database Modeling and Data Engineering
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningModel ValidationA/B TestingData AnalysisStatistical AnalysisAlgorithm Performance MonitoringData EngineeringExploratory Data AnalysisArtificial Intelligence IntegrationDocumentation Best Practices
Soft Skills
CommunicationCollaborationStrategic ThinkingProblem SolvingLeadership
Tools & Technologies
Power BITableauLookerMicrosoft ExcelGoogle Sheets
Industry Keywords
Banking Sector ExperienceData-Driven CultureTechnical MaturityComputational EfficiencyGovernance
Tech Stack
Tools & technologiesPythonSQLTableau
About the role
Key responsibilities & impact- Develop, validate, and deploy product propensity, churn, LTV, recommendation, clustering, and anomaly detection models
- Design analytical architecture and model validation strategies
- Define testing methodologies, including A/B tests, control/holdout groups, and hypothesis testing
- Monitor algorithm performance using metrics such as drift, precision, and recall
- Ensure scalability, continuous monitoring, computational efficiency, and governance of production Machine Learning workflows
- Identify business opportunities through exploratory analysis of large volumes of data
- Foster a Data-Driven culture and increase the team’s technical maturity
- Establish best practices for coding, modeling, documentation, and experiment reproducibility
- Incorporate Artificial Intelligence tools and workflows into the daily analytical process
- Translate technical concepts into strategic direction and present results and recommendations to leadership and business teams
Requirements
What you’ll need- Bachelor’s degree in a quantitative or technology-related field, such as Computer Science, Engineering, Statistics, Mathematics, Physics, or a related field
- Advanced proficiency in Python or R for data analysis, modeling, and routine development
- SQL (Structured Query Language)
- Advanced proficiency with BI and data visualization tools: Power BI, Tableau, or Looker
- Advanced proficiency with spreadsheets: Microsoft Excel or Google Sheets
- Database modeling and data engineering
- Experience in the banking sector is a plus
Benefits
Comp & perks- Meal and food allowance (if preferred, you may receive both amounts on a single meal benefits card)
- Health insurance
- Dental insurance
- Childcare assistance
- Life insurance
- Private pension plan
- Wellhub
- Mercantil Development Academy
- Profit Sharing Plan (PLR)
- Positions also available for people with disabilities