Open to opportunities

Denise Ray

@deniseray

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I build data and ML applications—turning messy data into dashboards, predictions, and production-ready insights.

Indonesia

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What I'm looking for

I’m looking to contribute to AI, data, and software projects in global remote teams—building dashboards and predictive applications with continuous iteration, experimentation, and problem-solving that turns insights into real outcomes.

I’m a builder-minded technology professional who transforms ideas into functional software through continuous iteration, experimentation, and problem-solving. I’m driven by turning data into decisions through practical analytics, machine learning, and clear dashboard experiences.

I’ve developed 11 end-to-end analytics and machine learning applications across logistics, retail, healthcare, marketing, hospitality, sports, and customer analytics. My work spans data cleaning, validation, exploratory analysis, and feature engineering—so models and dashboards stay grounded in real-world signals.

In logistics, I built a Streamlit performance dashboard with KPI monitoring, interactive filtering, and multi-dataset comparisons, then engineered time-based features to support a Decision Tree model for shipment delay factors. For forecasting, I created a sales pipeline using realistic synthetic data and time series modeling (Prophet and ARIMA), paired with a Plotly Dash dashboard and scalable workflow thinking.

I also create predictive and segmentation-focused products, from conversion prediction in digital marketing to churn modeling with class imbalance handling (SMOTE and class weighting) and model comparisons. Beyond analytics, I enjoy AI-assisted development—prompt engineering, LLM application development, workflow automation, and rapid prototyping—especially in global remote environments.

Experience

Work history, roles, and key accomplishments

Sales Forecasting Pipeline

Denise Ray Indonesia

Created an end-to-end sales forecasting pipeline using synthetic data with trend, seasonality, promotion, holiday, and noise components. Trained and evaluated Prophet and ARIMA time-series models and delivered an interactive Plotly Dash dashboard with scalable workflow examples (Apache Spark).

Python Pandas NumPy Prophet ARIMA Plotly MAE (Mean Absolute Error)RMSE (Root Mean Square Error)Apache Spark Time Series Modeling Synthetic Data

Shipping Performance Dashboard

Denise Ray Indonesia

Built a Streamlit logistics analytics dashboard with shipment KPI monitoring and interactive multi-dataset comparisons. Developed feature-engineered delivery/temporal features and a Decision Tree model to identify factors associated with shipment delays.

Python Streamlit Pandas scikit learn Matplotlib SeaBorn Plotly Decision Trees Feature Engineering

ChurnLens Predictive Modeling

Denise Ray Indonesia

Developed a customer churn prediction pipeline with exploratory data analysis and feature engineering. Handled class imbalance using SMOTE and class weighting, evaluated multiple classifiers, and translated feature importance into customer retention recommendations.

Python Pandas scikit learn Logistic Regression Random Forest Gradient Boosting LightGBM SMOTE GridSearchCV Feature Engineering Model Evaluation

Digital Marketing Performance Dash

Denise Ray Indonesia

Built a Streamlit digital marketing analytics application with campaign monitoring, keyword optimization, customer behavior analysis, and audience segmentation. Implemented conversion prediction with feature engineering, automated preprocessing, and a deployed predictive model.

Python Streamlit Pandas Matplotlib SeaBorn scikit learn Machine Learning Feature Engineering Data Analysis

A/B Testing Framework UI Rollout

Denise Ray Indonesia

Implemented an A/B testing framework to support UI feature rollout analysis. Used statistical tooling to enable testing workflows across experiments.

Python SQL Scipy A B Testing

Hotel Booking Analysis Dashboard

Denise Ray Indonesia

Created an end-to-end hotel booking analytics application using Streamlit. Engineered booking features and hospitality KPIs, analyzing cancellation, seasonality, pricing behavior, revenue, OTA platform performance, and guest segmentation.

Python Streamlit Pandas Matplotlib SeaBorn Feature Engineering Data Analysis KPI Analysis

Anomaly Detection Synthetic Sales

Denise Ray Indonesia

Built an anomaly detection project on synthetic sales data and visualized results in an interactive Plotly Dash interface. Used Isolation Forest modeling to identify anomalies.

Python scikit learn Isolation Forest Plotly Anomaly Detection

Soccer Analytics Dashboard

Denise Ray Indonesia

Built an interactive soccer event analytics dashboard using R Shiny. Engineered event sequence and n-gram features and created multiple interactive modules with dynamic filtering and Plotly visualizations.

R Shiny Dplyr Ggplot2 Plotly Data Visualization Feature Engineering

Price Intelligence Dashboard

Denise Ray Indonesia

Built a price intelligence dashboard to support basket price optimization. Developed the application in Python with Streamlit and interactive visualizations using Altair.

Python Streamlit Pandas Dashboard Development Data Visualization

Healthcare KPI Analysis

Denise Ray Indonesia

Conducted healthcare financial and operational KPI analysis using SQL and Python. Focused on business analytics-style reporting and KPI computation.

SQL Python KPI Analysis Business Analytics

Restaurant Sales Analysis

Denise Ray Indonesia

Performed restaurant sales analysis from raw data through business insights. Included SQL-based data handling with SQLite and delivered business intelligence outputs.

Python SQL SQLite Business Intelligence