Data Analytics Portfolio

Hervé Alcé

Data Analyst • Business Intelligence • Predictive Analytics

I combine data analytics with professional experience in quality, manufacturing, operations and leadership. My work focuses on transforming complex data into clear insights, predictive models and practical recommendations that organizations can use to make better decisions.

Where Data Meets Operations

My path into analytics is built on more than technical training. Before specializing in data analytics, I worked in chemistry, manufacturing, production management and quality assurance.

Those experiences taught me how organizations actually use data: identifying process failures, monitoring performance, investigating root causes, evaluating risk and making decisions that affect operations, quality and customers.

I am now applying that business and scientific background to data analytics, machine learning, visualization and predictive modeling.

M.S. Data Analytics
B.A. Chemistry
R + Python Analytics & Modeling
Leadership Quality & Operations

Featured Projects

Selected projects demonstrating data preparation, statistical analysis, machine learning, visualization, model deployment and business interpretation.

PROJECT 01

Flight Delay Prediction & MLOps Pipeline

Developed a reproducible machine-learning pipeline using U.S. flight data to predict departure delays. The project included data preparation, model training, experiment tracking, API development, unit testing and containerization.

Python Machine Learning MLflow Docker REST API Git
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PROJECT 02

Healthcare Readmission Analytics

Analyzed healthcare data to investigate patterns associated with patient readmission. The project combined data preparation, exploratory analysis, visualization and interpretation to identify meaningful trends and communicate findings.

Data Visualization Healthcare Analytics Tableau EDA
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PROJECT 03

Medical Data Predictive Modeling

Prepared and analyzed medical data for predictive modeling using R. The workflow included data inspection, cleaning, feature preparation, train/test splitting, model development and performance evaluation.

R Tidymodels Random Forest Data Cleaning Model Evaluation
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PROJECT 04

Statistical & Predictive Analysis

Applied regression, dimensionality reduction and statistical techniques to structured datasets to identify important variables, reduce complexity and build interpretable predictive models.

R Regression PCA Statistics Predictive Analytics
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Technical & Business Skills

Data Analytics

Data cleaning
Exploratory analysis
Statistical analysis
Predictive modeling
Model evaluation

Programming

R
Python
Tidymodels
Pandas
Data transformation

Visualization

Tableau
Excel
Dashboards
KPI reporting
Data storytelling

Data Operations

MLflow
Git / GitLab
Docker
APIs
Reproducible pipelines

Professional Perspective

Quality Assurance & Production Leadership

Manufacturing • Laboratory • Regulated Environments

My professional background includes leadership in production and quality assurance environments where data is essential to daily decision-making. I have worked with quality metrics, CAPA tracking, deviations, nonconformances, calibration records, documentation, root-cause investigations and process improvement.

This experience allows me to approach analytics from both a technical and operational perspective. I understand that an analysis is only valuable when it helps an organization make a better decision.

Education & Credentials

Master of Science — Data Analytics

Western Governors University


Bachelor's Degree — Chemistry


Additional Professional Training

ISO 9001:2015 Certified Auditor • Quality Management • Process Improvement • Regulatory Compliance

Let's Turn Data Into Decisions.

I am interested in opportunities involving data analytics, business intelligence, healthcare analytics, manufacturing analytics, quality analytics and operations.