Artificial Statistical Analyst In Latin America
At Inti, our Statistical Analysis service leverages proven
quantitative techniques—like k-means clustering, principal
component analysis, and regression modeling—to uncover
deep patterns, segment your data, and deliver actionable
insights you can trust.
Why Statistical Analysis Matters
Even the largest datasets hold hidden stories. With robust statistical methods, you can:
- Reveal customer segments that drive targeted marketing
- Identify key drivers of sales, churn, or quality issues
- Simplify complexity by reducing dimensionality for clearer interpretation
Our Two-Pronged Approach
Exploratory Data Analysis (EDA)
- Summary statistics, visualizations, and correlation matrices to understand distributions and relationships
- Outlier detection and transformation recommendations to prepare for modeling
Statistical Modeling & Segmentation
- K-Means Clustering to group similar observations and discover natural segments
- Principal Component Analysis (PCA) to reduce dimensionality and highlight principal drivers
- Regression Models (linear, logistic, multivariate) to quantify relationships and predict numerical or categorical outcomes
Our Methodology
Data Preparation & EDA
- Clean and normalize input variables
- Generate descriptive tables, histograms, and scatterplots
- Compute correlation and variance metrics to spot multicollinearity
Feature Transformation
- Apply PCA to condense variables into orthogonal components
- Scale and standardize features for meaningful clustering and regression
Clustering & Modeling
- Run k-means (and other distance-based techniques) to segment data into actionable cohorts
- Fit regression models to test hypotheses and estimate effect sizes
- Evaluate goodness-of-fit (R², adjusted R², AIC/BIC) and cluster validity (silhouette score)
Data Governance & Security
- Perform cross-validation and hold-out tests for model robustness
- Create intuitive dashboards and reports translating statistical output into business language
- Recommend next steps: monitoring plans, threshold alerts, or data-driven policies
Tools and Technologies
Languages & Libraries
NumPy
Pandas
Python
Clustering & Dimension Reduction
Scikit-learn
Pytorch
TensorFlow
Visualization
Matplolib
ggplot2
Ploty
Collaboration & Versioning
Git
Jupiter
Rstudio
Benefits You ll See
- Clear customer or product segments for targeted campaigns
- Quantified insights on variables driving key metrics
- Streamlined datasets that cut noise and focus on what matters
- Empowered decision-making supported by statistical rigor
Case Study Highlight
Customer Segmentation for E-Commerce
An online retailer asked Inti to segment its 1M+ customer base. We:
Conducted EDA to identify purchase behaviors and demographic patterns
Applied k-means to reveal four distinct segments (e.g., “Value Shoppers,” “Premium Loyalists”)
Used regression to quantify what drives lifetime value in each group
Result: Tailored promotions lifted average order value by 18% within three months.
Frequently Asked Questions
We use elbow and silhouette methods to recommend an optimal range, then validate with business context.
Not always—but when you have dozens of correlated variables, PCA helps focus on the components that explain most variance.
Absolutely. We translate results into clear narratives, supported by visual dashboards.
Begin your journey with Inti today
Talk to an expert for free!
About
Inti Consulting Services LLC is a company based out of Miami, FL. We aim to provide US companies with advanced talent from Latin America to take advantage of the amazing talent that exists in the region.