Hi, I'm Melissa Slawsky.
Strategy and operations specialist, accelerating value, growth, and performance for forward-thinking organizations navigating critical inflection points.
- Strategic growth frameworks and performance analytics
- Real-time dashboard development for proactive decision-making
- Data-driven optimization systems for scaling operations
- Converting analytics into actionable business intelligence
- Predictive modeling for strategic decision support
Showcasing progression from service design to data-driven insights, highlighting automation and efficiency gains while maintaining quality and client experience.
- Service Design & Process Optimization
- Analyzed qualitative and quantitative data to uncover customer behavior patterns
- Developed advanced algorithms aligning business value with user needs
- Delivered actionable insights through real-time analytics and intuitive dashboards
Strategic market analysis leveraging business intelligence to identify growth opportunities and optimize market positioning.
- Transformed Excel data into interactive visualizations revealing pricing trends and market opportunities
- Mapped geographical concentrations to identify underserved neighborhoods
- Developed data-driven framework for strategic market expansion
- Created stakeholder-ready dashboards enabling informed decision-making
Implementation of 80/20 analysis for sustainable growth, demonstrating systematic approach to value creation.
- Applied 80/20 principle for 75% performance improvement
- Created interactive Tableau dashboards for real-time insights
- Developed data-driven recommendations for resource optimization
Determining ROI and most impactful marketing channels through advanced statistical analysis and ML.
- Applied linear regression to optimize marketing budget allocation for maximum sales impact
- Developed predictive models identifying most effective marketing channels
- Quantified ROI for different marketing strategies with statistical precision
- Enabled data-driven decision-making for strategic resource allocation
Leveraging machine learning models to predict churn and optimize retention strategies for financial institutions.
- Applied Random Forest and Logistic Regression models for churn prediction with 87% accuracy
- Developed predictive models identifying at-risk customer segments and most important features
- Enabled proactive retention by pinpointing high-risk segments and tailored interventions
Predicting key drivers of employee retention using regression analysis and machine learning.
- Developed machine learning models predicting employee turnover with 85% accuracy
- Identified critical factors driving workforce attrition in automotive manufacturing
- Transformed predictive insights into strategic HR retention strategies
- Leveraged Random Forest and Logistic Regression for advanced workforce analytics
Advanced Statistical Analysis 📊
- NBA Career Longevity Analysis: Applied multivariate statistical techniques, including logistic regression and survival analysis, to decode NBA career sustainability and identify key leverage points.
- Marketing Budget Impact Analysis: Used linear regression and hypothesis testing to optimize marketing spend for maximum ROI.
- Predicting Employee Turnover: Conducted ANOVA and chi-square tests to identify turnover patterns and validate predictive models.
Descriptive Analytics 📈
- Airbnb Market Analysis (Athens): Visualized key trends and customer preferences to identify underserved areas and market opportunities for Athens Airbnb.
- Google Fiber Dashboard Analysis: Analyzed performance metrics to identify bottlenecks and prioritize resource allocation, enabling targeted improvements in service delivery and operational efficiency.
Diagnostic Analytics 🔬
- NBA Career Longevity Analysis: Decoded NBA career sustainability using classification modeling and factor analysis, highlighting efficiency metrics as a key leverage point for talent strategy.
- Predicting Employee Turnover: Developed machine learning models (Random Forest, Logistic Regression) to identify key turnover drivers for an automobile manufacturer, enabling proactive retention strategies.
Predictive Analytics (Supervised ML) 🤖
- Airline Customer Satisfaction: Utilized ML models to predict customer satisfaction, identifying key drivers and providing actionable insights to enhance customer experience.
- Bank Customer Churn Prevention: Leveraged ML models to identify at-risk customers and optimize retention strategies.
- Waze User Analytics: Leveraged ML to predict user churn, uncover behavioral patterns, and provide actionable insights.
- Predicting Employee Turnover: Identified turnover drivers for strategic retention solutions.
- NBA Career Longevity Analysis: Explored factors influencing NBA career longevity for talent strategies.
Prescriptive Analytics 📋
- Marketing Budget Impact Analysis: Applied linear regression and statistical analysis to optimize budget allocation for maximum sales impact.
- Traffic Volume Study: Visualized historical traffic trends to optimize resource planning during peak times.
Clustering Approaches (Unsupervised ML) 📊
- K-Means Color Compression: Leveraged clustering to extract color palettes for efficient image compression.
- Penguin Clustering with K-Means: Used clustering to segment penguin populations by species/sex for conservation priorities.
Exploratory Data Analysis (Qualitative Research) 🔍
- Qualitative Dissertation Research: Conducted thematic analysis using Nvivo on 20+ hours of interview data, uncovering insights for program improvement and professional development.
Integrated Analytics Projects 🌐
- Marketing Budget Impact Analysis: Combines descriptive, diagnostic, and prescriptive analytics for channel optimization.
- Time Optimization Analyses:
Strategic Innovation 💡
- Innovation Systems
- Tech-enabled Consulting
- Value Modeling
- Performance Optimization
- Workflow Automation
Advanced Statistical Analysis 📐
- Multivariate Analysis (e.g., PCA, Factor Analysis)
- Regression Models (Linear, Logistic, Ridge, Lasso)
- Hypothesis Testing (t-tests, ANOVA, chi-square)
- Time Series Analysis & Forecasting
- Survival Analysis & Reliability Analysis
- R, Python (statsmodels, scipy)
- SPSS, SAS
- Excel (Advanced Statistical Functions)
Analytics & Intelligence 📊
- Business Intelligence
- Advanced Analytics
- Predictive Modeling
- Real-time Dashboards
- Tableau
- BigQuery
- Airtable (Relational Databases)
- SQL, Python (Data Preparation)
- Power BI
- Data Cleaning & ETL
- Data Visualization & Storytelling
- Forecasting & Segmentation
- Hypothesis Testing
Operations Excellence 🔄
- Process Optimization
- System Design
- Resource Allocation
- Performance Analytics
- Real-time Insights
Research Methods 🔍
- Qualitative Methods
- Quantitative Analysis
- Thematic Coding
- Interview Methods
- Market Intelligence
- Pattern Recognition
© Melissa Slawsky 2025. All Rights Reserved.