Eric Solano

(919) 491-6481 -

Summary

Analytical and resourceful professional with experience working with data and applying predictive analytics, mathematical modeling, statistical inference, machine learning, operations research and engineering. Experience with multiple information technology tools to work in a variety of projects across multiple industries. Experience in applying data analysis methodologies to extract knowledge from operational data to help decision making for the enterprise business development.

DemonstratedAbilities

  • Strong mathematical background, analytical and problem solving skills.
  • Experience in the implementation of machine learning algorithms and data mining systems.
  • Knowledge of Operations Research techniques to analyze complex decision and solution spaces in multi-objective problems to find optimal and near optimal solutions.
  • Knowledge of Statistical Inference to leverage synergy between statistics and data mining and transform data mining into knowledge discovery.
  • Use of statistical analysis, simulation and optimization to create predictive models that extend the benefits of descriptive analysis and statistics.
  • Knowledge of Systems Dynamics to explain the characteristics and inter-dependencies of the different components in a business process and to analyze business dynamics.
  • Experience with a variety of dashboards and visualization technologies to summarize data analysis through simple but powerful visual tools.

Software AND ANALYTICAL Expertise

  • Machine Learning: Supervised and Unsupervised Learning. Regression and Classification Algorithms. Feature Selection and Engineering. Dimensionality Reduction. Model selection and tuning parameters.
  • Mathematical optimization techniques: linear, integer, and dynamic programming; genetic algorithms; multiobjective programming and modeling to generate alternatives. Optimization tools: CPLEX, COIN LP.
  • Predictive Modeling and Analytics Tools: Repast, AnyLogic, eclipse, Systems Dynamics, Discrete Event Modeling, Agent-Based Modeling.
  • Statistical techniques and tools: MATLAB, SAS, R, survival analysis, time series analysis.
  • Business Intelligence tools: ORACLE, spreadsheets, Tableau, R.
  • Database systems/tools: Oracle, MySQL, PostgreSQL, SQL Server, MS Access.
  • Operating systems: Windows, UNIX, LINUX (Debian Ubuntu).
  • Programming languages: Object-oriented programming; Java, Visual Basic.NET; Other languages: Visual Basic 6.0, VBA, PL/SQL.
  • Geographic Information Systems (GIS): ESRI Software, Oracle Spatial.
  • High-performance computing tools: MATLAB Distributed Computing Toolbox, MATLAB Simulink
  • Data Visualization: tableau, shiny, R, D3.js

ProfessionalExperience

Independent Consultant, Seattle Area, WA 2015 – present

Data Analyst / Scientist

  • Price Optimization for Retail Analytics
  • Impact: Optimized profit and revenue margins for retail business owners with methodological framework to make informed decisions on product price selection and product assortment.
  • Tools: regression and classification algorithms, mathematical optimization, R, linear programming.
  • Software Engineering Defect Prediction
  • Impact: Reduced software testing costs for software producers and engineers with tools to help make decisions about software testing resource allocation and optimization.
  • Tools: classification algorithms.
  • Consumer’s Sentiment Analysis of Mobile Phone Brands using Social Media Data
  • Impact: Provided phone manufacturers with tools to help make decisions about benchmarks, future marketing campaigns and optimization of segmentation and targeting.
  • Tools: Polarity and sentiment analyses, social media.

RTI International, Research Triangle Park, NC 1999 – 2015

Research Analyst

  • Waste Management Operations and Business Optimization
  • Impact: Reduced waste management and engineering costs for business operations and municipalities with improved decision making in technology adoption, potential new markets and regulation compliance.
  • Tools: machine learning, optimization, business intelligence, simulation modeling and life cycle analysis.
  • Electric Power Load Forecasting
  • Impact: Reduced capital and maintenance costs for electric grid planners with load forecasting tools to help make decisions on capital investment, network maintenance, etc.
  • Tools: machine learning, regression models, simulation modeling etc.
  • Lifetime Predictive Modeling of LED Lighting
  • Impact: Reduced manufacturing costs for lighting industry with decision support tool to help make decisions on product choices, physical properties and material selections to optimize lifetime.
  • Tools: Regression models, survival analysis, simulation models.
  • Cost Effectiveness of Screening for Breast Cancer
  • Impact: Improved patient quality of life and reduced healthcare costs with tools to help make decisions about cancer treatments and interventions.
  • Tools: agent based models and micro-simulation, risk analysis, stochastic considerations.

Education

Ph.D., Systems Analysis/Engineering, North Carolina State University

M.S., Civil and Environmental Engineering, North Carolina State University

B.S., Civil Engineering, University of Costa Rica

Relevant Publications And Presentations

Davis, J. L., Mills, K. C., Lamvik, M. K., Yaga, R. W., Shepherd, S. D., Bittle, J. F., Baldasaro, N. G., Solano, E., et al. (2014, April). System reliability for LED-based products. Presented at EuroSim 2014, Ghent, Belgium.

Solano, E., Ranjithan, S.R., Barlaz, M.A., & Brill, E.D. (2002). Life-cycle-based solid waste management. I: Model development. Journal of Environmental Engineering, 128, 981–992.

Note: For a full list of publications and presentations visit my at .

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