đź’¦ FULL SET: Resume/gregory kott - Uncensored 2025

Gregory Kott

Verified Expert  in Engineering

Bio

Greg is a senior data analytics consultant with over 26 years of experience delivering advanced analytics solutions to Fortune 500 companies and government agencies. Specializing in business intelligence, workforce optimization, and decision-support modeling, he transforms complex operational data into strategic insights. Greg applies a broad range of analytical methods, modeling techniques, and visualization approaches to drive data-informed decisions and improve organizational performance.

Portfolio

Conduent
Data Analytics, Business Intelligence (BI), Data Processing Automation...
Xerox
Algorithms, Data Analytics, Predictive Modeling, Cost Analysis...

Experience

  • Data Analytics - 20 years
  • Problem Solving - 20 years
  • Process Simulation - 10 years
  • Exploratory Data Analysis - 10 years
  • Business Intelligence (BI) - 10 years
  • Workforce Analytics - 10 years
  • Operations Research - 5 years
  • Data Processing Automation - 5 years

Availability

Part-time

Preferred Environment

Python, Microsoft Power BI, Excel 365

The most amazing...

...thing I developed is a reliability and cost model for Xerox’s first tandem printer, predicting performance, costs, and margins that led to improvements.

Work Experience

Principal Data Scientist

2017 - 2025
Conduent
  • Enhanced workforce management strategies by developing high-resolution performance metrics through log transformations and binormal statistical modeling.
  • Developed an optimization process to improve efficiency by dynamically assigning cross-trained back-office agents to daily queues and implementing a weekend strategy that offered overtime exclusively to selected, willing employees.
  • Integrated multi-source operational data to build a tool that evaluates agent utilization and performance across in-office and remote teams, leveraging workforce management data to identify trends in efficiency, quality, and time allocation.
  • Built a predictive attrition model that informed targeted supervisor interventions, helping reduce turnover and increase agent retention.
Technologies: Data Analytics, Business Intelligence (BI), Data Processing Automation, Workforce Management (WFM), Machine Learning, System Modeling, Microsoft Power BI, Azure Data Lake, SQL, Azure, Data Engineering, Data Science, Microsoft Azure, Data Modeling, Predictive Analytics, Forecasting, BI Reporting, ETL, Data Visualization, Solution Architecture, Data Pipelines, Monte Carlo Simulations, Time Series Forecasting

Principal Research Scientist

1998 - 2016
Xerox
  • Designed advanced performance models for Sprint and Apple contact centers to support pay-for-performance programs, leveraging customizable KPIs and adaptable implementation strategies.
  • Developed a preliminary logistics platform to track, monitor, and forecast domestic freight movement while assessing disruption impacts across a multi-modal transportation network.
  • Researched the feasibility of condition-based maintenance as a reliability strategy for the printing industry.
  • Engineered data analytics models to estimate maintenance service costs and assess the performance of Xerox printing systems, supporting the development of product business cases.
  • Architected population aging models for Xerox systems to measure the impact of customer adoption and service engineering learning curves on reliability and maintenance as new customers are added monthly, improving forecasting and support strategies.
Technologies: Algorithms, Data Analytics, Predictive Modeling, Cost Analysis, Process Simulation, Business Intelligence (BI), Data Engineering, Data Science, Data Modeling, SQL, BI Reporting, ETL, R, Predictive Maintenance, Artificial Intelligence (AI), Monte Carlo Analysis

Experience

Optimizing Workforce Scheduling in a Cross-trained Environment

I developed the initial feasibility models for a Workforce Management (WFM) resource scheduler designed to optimally assign agents to work queues in a cross-trained environment. The models incorporated daily workload requirements and portions of existing backlog, demonstrating up to 30% efficiency gains.

Building on this success, I led a small team to integrate the solution into the business group's WFM tool. The implementation also enabled a new weekend overtime strategy—replacing mandatory shifts with optional, higher-rate assignments for top-performing staff—enhancing performance and morale.

Education

1992 - 1998

PhD in Mechanical Engineering

Rensselaer Polytechnic Institute (RPI) - Troy, NY, USA

1982 - 1987

Bachelor's Degree in Mechanical Engineering

Rochester Institute of Technology (RIT) - Rochester, NY, USA

Skills

Tools

Microsoft Power BI, MATLAB, Tableau, Jupyter

Paradigms

Business Intelligence (BI), ETL

Languages

Python, SQL, R

Platforms

Azure, Jupyter Notebook

Storage

PostgreSQL, Data Pipelines

Other

Data Analysis, Problem Solving, Data Analytics, Data Engineering, Data Science, Data Modeling, Forecasting, BI Reporting, Workforce Analytics, Dashboards, Data-driven Dashboards, Exploratory Data Analysis, Data Visualization, Predictive Maintenance, Solution Architecture, Monte Carlo Analysis, Monte Carlo Simulations, Time Series Forecasting, Excel 365, Optimization, Operations Research, Algorithms, Data Processing Automation, Workforce Management (WFM), System Modeling, Process Simulation, Microsoft Azure, Predictive Analytics, Random Forest Regression, Time Series Analysis, Decision Tree Classification, Mathematics, Programming, Computational Methods, Formulating Novel Problems, Machine Learning, Azure Data Lake, Predictive Modeling, Cost Analysis, Geospatial Data, Artificial Intelligence (AI)

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