Phone: 419-***-****, Email: firstname.lastname@example.org
Skilled Data Scientist with 3 years of experience in executing data-driven solutions. Experienced at creating machine learning models, using predictive data modeling, and analyzing data mining algorithms to deliver insights and implement action-oriented solutions to complex business problems.
Proficient in Machine Learning Modeling Algorithms such as Regression models, SVM, K-NN, Decision Trees, K-Means, Boosting and Ensemble methods such as Random Forest, XGBoost and other advanced statistical techniques using Python.
Proficient in Python programming to analyze data, visualize data, and develop machine learning algorithms using different libraries such as Pandas, Scikit-learn, XGBoost, NumPy, SciPy, Matplotlib, and Seaborn.
InterContinental Hotels Group (IHG) - Atlanta, GA Jan 2017- Present
Analyzed main Revenue Management Indicators (ARI, MPI, and RGI) of hotels to determine their performance against competitors at a high level and advised on opportunities to drive higher occupancy and revenue.
Studied hotels performance and their services individually along with customer behaviors and spending activities to analyze potential opportunities and recommend new strategies accordingly.
Applied various Statistical and Machine Learning techniques (e.g. Logistic Regression, Random Forest, SARIMA) to identify trends and patterns in several million surveys received from guests staying at more than 4,000 IHG hotels in America’s region.
Developed new KPIs to measure performance of suggested promotional initiatives for IHG’s specific hotel brands.
Performed ad-hoc analyses and prepared related reports upon request of Sales & Marketing, Analytics and Finance Departments for different purposes such as impact analyses and feasibility studies.
Designed, developed and deployed supervised machine learning models in Python using various algorithms such as Random Forest, Linear Regression, and Logistic Regression.
Developed various statistical algorithms to model volatility of hotels’ financial performance and effect of seasonality.
Designed several A/B tests for marketing purposes and participated in all phases of data mining; data collection, data cleaning, developing models, validation and visualization.
Published various Tableau dashboards on the server using Advanced Tableau tools (e.g. Tabular Calculations, Parameters, Stories) for different types of audiences across organization.
Pathways Financial Credit Union - Columbus, OH Jan 2016- Dec 2016
Description: The main objective of the project was to improve institutions' efficiency by reducing default rate and assessing risks while offering products by developing new and existing machine learning algorithms based on the business historical data.
Develop and improve predictive machine learning models including Predictive Recovery Return (PRR) and Probability of Default (PD) with tight collaboration with Underwriting, Finance, and Risk Assessment teams.
Enhanced the Offering Model using supervised machine learning algorithms to optimize profitability and generate more competitive offers.
Performed K-NN classification to segment customers and flag them based on their transactions, industry, etc. and improve fraud detection framework accordingly.
Performed various data analysis to develop time series and get a better insight into the business.
Prepared various monthly ad-hoc financial reports and recommendations on analytic projects.
Develop and maintain financial reports to clearly communicate actual results and forecasted performance.
Ohio University – Athens, OH - Master of Science in Mechanical Engineering GPA: 3.9
Isfahan University of Technology – Isfahan, Iran - Bachelor of Science in Mechanical Engineering GPA: 3.7
Programming Languages: Python, Matlab
Big Data Ecosystems: Hadoop (Hive), Spark, PySpark
Database Platforms: MySQL, SQL Server
Reporting Tools: Tableau, MS Excel, MS PowerPoint