Senior Data Scientist

Rappi; Bogotá; Presencial; COP 120.000.000 - 180.000.000; Jornada completa

Descripción de la vacante

Rappi is seeking a data-driven analytics professional to lead experimentation design and analysis in Bogotá. You will ensure validity through SRM checks and bias assessments, and you will quantify the GMV impact of findings to guide product decisions.

You will combine SQL-heavy cohort analysis with vectorized Python to evaluate price elasticity, demand curves, and conversion effects while collaborating with Product Managers to turn insights into strategy.

Formación

• Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative field.
• 3+ years in Product Analytics, Data Science, or Growth focusing on A/B testing and causal inference.
• Experience with SRM checks, novelty/primacy effects, and bias assessment in experimentation.

Responsabilidades

• Lead the design and analysis of A/B tests with rigorous statistical standards.
• Investigate drops in core metrics and quantify GMV impact to prioritize fixes.
• Analyze price elasticity and demand curves to optimize pricing decisions.
• Write high-performance SQL for cohort analysis and data preparation for testing.
• Develop vectorized Python scripts for large-scale datasets (10M+ rows).
• Collaborate with Product Managers to translate statistical insights into actionable recommendations.
• Optionally design AI-driven workflows (N8N/Airflow) to automate anomaly detection and monitoring.

Conocimientos

SQL

Python

Experimentation

Causal inference

Communication

Statistics

Educación

Bachelor’s degree in statistics, mathematics, economics, or computer science

Herramientas

N8N

Airflow

Pandas/Polars/NumPy

Descripción del empleo

• Experimentation Excellence: Lead the design and analysis of A/B tests with high statistical standards. You will not just calculate p-values, but rigorously check for Sample Ratio Mismatch (SRM), Novelty/Primacy effects, and biases to ensure validity before rollout.
• Diagnostic & Root Cause Analysis: Proactively investigate sudden drops in core metrics (like Retention or Conversion). You will differentiate between technical issues (bugs, latency) and market behaviors/competitor actions, and quantify the GMV loss to prioritize engineering fixes.
• Economic Strategy: Analyze price elasticity and demand curves to recommend optimal pricing points. You will balance trade-offs between Conversion Rate lift and Operational Costs (e.g., support tickets, refunds) to maximize long-term profitability.
• Advanced Data Processing: Write high-performance SQL for complex cohort analysis and data aggregation. You will develop optimized Python scripts (using vectorization instead of loops) to handle large-scale datasets (10M+ rows) efficiently.
• Strategic Partnership: Act as a thought partner for Product Managers. You will challenge assumptions with data, translating complex statistical concepts (Welch’s t-test, confidence intervals) into actionable business recommendations.
• Automation & Innovation: (Optional but valued) Design workflows using AI Agents (N8N, LLMs) or Python scripts to automate anomaly detection and metric monitoring.
• Educational Background: Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, or a related quantitative field.
• Experience: 3+ years in Product Analytics, Data Science, or Growth, with a specific focus on A/B Testing and causal inference.

Perfil Tech

• Technical Stack:
• SQL Expert: Ability to write complex window functions, manage sparsity in cohort retention, and prepare data for statistical testing.
• Python Proficiency: Strong skills in Pandas/Polars/NumPy. You understand computational complexity ($O(N^2)$ vs $O(N)$) and know how to vectorize operations to optimize performance.
• Business Acumen: Ability to calculate the financial impact of technical decisions. You understand concepts like LTV, CAC, and Price Elasticity of Demand.
• Communication: Demonstrated ability to explain "why" a test failed or succeeded to non-technical stakeholders, moving beyond the numbers to the strategic implication.
• Plus: Experience with Workflow Automation (N8N, Airflow) or building simple RAG/AI agents for internal tools.