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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 computational efficiency. Proficient in translating complex data insights into strategic recommendations for business stakeholders.
Highest-signal resume keywords
Machine Learning Model DevelopmentPython or R ProficiencySQL ExpertiseData Visualization Tools ProficiencyDatabase 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 LearningData AnalysisModel ValidationStatistical AnalysisA/B TestingHypothesis TestingPerformance MetricsData EngineeringExploratory Data AnalysisArtificial Intelligence Tools
Soft Skills
CommunicationCollaborationProblem-SolvingStrategic ThinkingAdaptability
Tools & Technologies
Power BITableauLookerAdvanced ExcelGoogle Sheets
Industry Keywords
Banking Sector ExperienceData-Driven CultureTechnical MaturityGovernanceComputational Efficiency
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 the analytical architecture and model validation strategy, defining A/B tests, control/holdout groups, hypothesis tests, and performance metrics such as drift, precision, and recall
- Ensure scalability, continuous monitoring, computational efficiency, and governance of production Machine Learning routines
- Identify business opportunities through exploratory analysis, uncovering hidden patterns, bottlenecks, and growth levers across large volumes of data
- Promote a Data-Driven culture and enhance the team’s technical maturity by defining best practices for coding, modeling, documentation, and experiment reproducibility
- Incorporate Artificial Intelligence tools and workflows into the daily analytical workflow, accelerating model prototyping, code generation, documentation, and the exploration of unstructured data
- Translate technical concepts into actionable strategic direction, presenting results and recommendations to leadership and business stakeholders
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 discipline
- Advanced proficiency in Python or R for data analysis, modeling, and routine development
- Structured Query Language (SQL)
- Proficiency with BI and data visualization tools (Power BI, Tableau, Looker)
- Proficiency with spreadsheets (Advanced Excel/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 (PLR)