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Data scientist

Toronto, ON, Canada
March 13, 2019

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Machine Learning



Big Data


RNN Clustering

Reza Moshksar, PhD

Data Scientist

Dec 2017- Data Scientist

Present International Payment Solutions, Toronto, Canada

Applied sentiment analysis and text summarization on social media data.

Predicted credit rating of clients, based on transaction records and press releases.

Settled and ranked potential customers base on geolocation and social media search history, which increased revenue by 47%.

Software & Tools

I have over 5 years of data science and professional experience in advanced analytical, statistical modeling, and machine learning. I have knowledge of Big Data plus hands-on data analysis and software development experience with frameworks like Spark and scripting languages like Python. I enjoy working collaboratively in team environments and able to work independently to complete ad hoc requests and large projects. I am one of the top 10 most liked Wikipedia users in 2017 and 2018.


Data Scientist

Aug 2014-

Aug 2017 Rismun, Tehran, Iran

Constructed a predictive model based on the weather data. This model was part of a national project for optimizing energy consumption.

Applied to data extraction, feature engineering, predictive classification, regression modeling, model assessment, and model tuning.

Built natural language processing models to understand and extract relevant information from social media feeds and press releases. Skills

Machine Learning Deep Learning Big Data

Fraud Analytics Marketing Analytics Digital

Analytics Customer Segmentation Collection

Analytics Natural Language Processing (NLP)

Image Processing

Expertise in various statistical techniques:

Logistic Regression Decision Tree SVMs

Random Forest Gradient Boosting RNN

Neural Networks KNN Data mining


Python and data analytics frameworks such as:

Pandas Numpy Sklearn Tensoflow Keras

Pytorch Matplotlib Seaborn Scipy

PySpark MySQL Tableau

Ms-Office Excel RapidMiner

Web: JavaScript jQuery Git Flask

Sep 2013- Data Analyst

Aug 2014 Novin Dadeh Gostar, Tehran, Iran

Collected and cleaned various data types from different sources and web.

Create visualizations, reports, and dashboards

Sep 2009- Admin, Sysop, Bureaucrat, Tool and Bot developer Present


Designed and developed more than 60 live web-based bots to check user's edits, get page stats, detect anomaly edits, and list NSFW images name.

Developed bots to edit, create, and categorize pages using natural language processing (NLP).

Applied clustering technics to add category label to articles.

Identified keywords and topics of articles with 98% accuracy.

Deployed live bot and services on the cloud servers of Wikimedia. Education

Building, Environment, Science and Technology Dept. Politecnico di Milano, Milan, Italy

Sep 2009-

Sep 2013

Building Technology Engineering, PhD

Thesis: Calibration of Building Energy Simulation through Meta-Models Publications

Calibration and uncertainty analysis for

computer models, Mar 2013, Applied Energy


Advanced Statistical Machine Learning &

Pattern Recognition Algorithms & Data

Structures Computer Vision Data Science

Specialization Deep Learning Machine

Learning Artificial Intelligence (AI)

Visualization Data


Core tools: Python, Keras, Pytorch, Sklearn, NLTK, and Tableau Core tools: Python, Pytorch, Sklearn, SQL, NLTK, Git, PySpark, jQuery, and JavaScript Core tools: Python, Sklearn, SQL, NLTK, jQuery, and JavaScript Core tools: Python, Excel, and SQL

Personal Info


List of Rismun company’s projects in detail

At Rismun, I was a member of the data science team where we primarily focused on data science tasks of software development.

Project, Client: New UI with a client dashboard, Mellat Bank 2017 Goal: Creating a client dashboard and developing an OMNI channel platform to allow for similar experiences across different platforms

Duty: Data science leader

• Participated in the platform development

• Identified anomalous transactions

• Predicted client credit

• Clustered clients

Achievements: The developed platform increased client transactions by 180%.


Project, Client: Intelligent Information Observation, Research and development department of Power Ministry of Iran 2016-2017

Goal: Developing a database platform for researchers to explore research articles Duty: Data science leader

• Developed a platform to find related scientific articles using public APIs such as Scopus, PatentView, and Civilica

• Crawled websites and articles through RSS feeds and google scholar searches

• Developed a word recommendation for the search box

• Created opportunities to further summarize and clustering articles, extract keywords, and recommend the most related articles

Achievements: The platform has assisted research groups to stay up to date Project, Client: Monitoring energy consumption, Iran National Engineering organization 2015-2016 Goal: Developing tools for clients to monitor and reduce household energy consumption Duty: Data scientist

Phase 1: develop a model for weather data

• Collected, cleaned, and verified weather data from different data sources

• Handled missing values in multiple variables of the weather data

• Built a predictive weather model based on the cleaned weather data using SVM Phase 2: Classify clients on their consumption behavior

• Collected and cleaned data from Gas meters

• Categorized more than 8 million clients in 10 groups based on their consumption behavior Achievements: Enabled intelligent billing, which resulted in 28% decrease in household’s energy consumption

Reza Moshksar, PhD

Data Scientist

SQL Python Keras Pytorch Sklearn

SQL Python Keras NLTK Sklearn Gensim jQuery Javascript SQL Python Sklearn

Project, Client: Financial platform, Iran National Engineering organization 2015 Goal: Developing a paperless financial management software Duty: Data scientist

• Processed OCR results such as text cleaning, grammar, and spell checking

• Developed a model for anomaly detection and integrated it in a BI Dashboard

• Clustered city neighborhoods based on the number of building permits

• Developed models to predict future inventories in neighborhoods Achievements: Enabled the management team to detect a fraud, which saved 47% of the budget Reza Moshksar, PhD

Data Scientist

SQL Python Sklearn PySpark

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