Position Summary

Horatio is seeking a mathematically driven Data Analyst to transform complex data into strategic business intelligence. This role requires advanced statistical modeling (linear algebra, calculus, time-series forecasting) to solve problems. Key functions include designing automated workflows using Python and Google Cloud to optimize data architecture and drive growth. This role is responsible for transforming raw data into aesthetically pleasing and functionally effective "decision-ready" visual narratives.

Responsibilities:

• Data Automation & Integration: Design and implement ETL/ELT pipelines to streamline data extraction and transformation processes.
• Advanced Analytics: Apply inferential statistics and advanced modeling techniques, including regression analysis and Time Series Forecasting (ARIMA/SARIMA), to solve business challenges.
• Tool Development: Build and maintain Google Workspace automations using Python (gspread) and advanced Google Sheets functions (QUERY, BYROW, LAMBDA).
• Database Management: Write complex, engine-agnostic SQL queries to manipulate large datasets across PostgreSQL, MySQL, or BigQuery.
• Data Storytelling: Translate complex findings into intuitive, visually compelling dashboards that drive clarity and business strategy.
• Mathematical Application: Utilize graduate-level concepts in Linear Algebra and Calculus to optimize data models and algorithmic performance.

Required Skills & Experience:

• Python for Data Science (Mandatory): Intermediate to Advanced proficiency in Pandas, NumPy, Requests, and JSON handling.
• Google API Automation: Proven experience with gspread for Google Sheets manipulation.
• SQL & Databases: Intermediate ability to write complex queries and a solid understanding of relational database design (3NF).
• Advanced Google Sheets: Expert-level knowledge of advanced functions and visualization within the Google ecosystem.
• API Fundamentals: Solid understanding of RESTful API concepts, HTTP methods, and authentication.
• Statistical Foundation: Deep understanding of descriptive and inferential statistics (probability distributions, central tendency).
• High-Level Mathematics: Proficiency in Linear Algebra (matrix operations), Differential/Integral Calculus, and Optimization techniques.
• Data Visualization: Strong experience with Matplotlib, Seaborn, or Plotly.

Preferred Qualifications:

• Machine Learning: Theoretical or practical experience in Supervised (Classification) and Unsupervised Learning (Clustering).
• Emerging Tech: Familiarity with Deep Learning, Neural Networks, NLP, and Large Language Models (LLMs).
• Advanced Frameworks: Knowledge of Scikit-learn, SciPy, TensorFlow, or PyTorch.

Education & Experience

• Advanced, near-native English proficiency.
• Bachelor’s or Master’s degree in Mathematics, Statistics, Data Engineering, or a related quantitative field.
• 3+ years of experience in data-driven roles with a focus on automation and statistical modeling.
   

This is an on-site position in Bogota.