About the Candidate
SUMMARY OF QUALIFICATION
· Strong experience in Python, SQL, and MS Excel with a focus on data analytical skills, mathematical modelling, and optimization.
· Enthusiastic about working on projects that have positive impacts on Canadian’s lives.
· Experienced in cleaning and analysing datasets through the programing languages Python, SQL.
· Experienced in data visualization through data manipulation and building dashboards through real-time visualization tools such as Tableau and Microsoft Power BI.
· Experienced working with raw data and transforming it to valuable insight.
· Experienced working both in teams and individually while generating innovative ideas.
AREAS OF EXPERTISE
· Analyzing data
· Data Visualization
· Time Series Analysis
· Statistics modeling
· Predictive analysis
· Sentiment Analysis
Technical Skills
· Python (Jupyter Notebook, PyCharm, Google Colab, Visual Studio)
· SQL
· AWS Transcribe, comprehend, S3
· HTML5 & CSS3
· C programming language
· Tableau
· QDA miner
· Microsoft Office Suite: Excel, PowerPoint, Word, Outlook, and SharePoint
Work Experience
Data Analyst
May 2022-Present
CanadaWheels, Ottawa, Canada
· Annotating, training, testing, iterating, and production monitoring of time series forecasting
· Analyzing customer data to provide meaningful insights
· Work with structured and unstructured raw data to design and develop innovative predictive models, metrics, and dashboards to uncover actionable insights
· Visualize and report data findings creatively in a variety of visual formats that provide insights to the organization
· Continuously enhancing knowledge / expertise in own area and keeping current on emerging trends/developments and grow knowledge of the business, analytical tools, and techniques
Data Analyst
March 2021-April 2022
TripScript, Ottawa,Canada
· Identified business opportunities for the company after the pandemic using unsupervised machine learning technics by extracting data from social media and preprocessed the data by removing noises, and unnecessary text.
· Developed a machine learning model using Topic modeling and Chance discovery to find the most wanted topics to find the business opportunities.
· I designed a fully automatic AWS pipeline to fetch, denoise and transcribe all TripScript’s audio files by using AWS Transcribe + S3. The results were automatically pumped into AWS comprehend for sentiment analysis.
· Used various signal processing and NN to denoise the audio files and remove the silence segments to enhance the accuracy and minimize the cost.
· Used various analytical techniques to convert the sentiments to some actionable KPIs and metrics.
Junior Data Analyst
May 2019-Jan 2020
ProshaSoft, Tehran, Iran
· Gathered and analyzed data from clients that were originally stored in MySQL data base.
· Assisted in building analytics tools to manage data and streamline data analysis using Python.
· Conducted detailed analysis and research through real time visualization tools such as Tableau and provided business insights to assist the project manager with the successful implementation of the project.
· Ensured provision of appropriate analytical support and outcome recommendations for key stakeholders.
· Examined documents and reports and presented findings in Excel and PowerPoint.
Education
Master of Applied Business Analytics
Carleton University
Supervisor: Michael Weiss
Courses: Social Analytics, Integrated Product development, applied analytics, Machine learning
Jan2020-June2021
B.Sc. In Software Engineering
Tehran Azad University
Courses: Data Structure, Data mining, Data storage and retrieval, Advanced programming, Algorithm design
Sep2013-Oct2018
Conference and Publication
• Pournemat, M., & Weiss, M. (2021). Identifying business opportunities using topic modeling and chance discovery. In ISPIM Conference Proceedings (pp.1-11). The International Society for Professional Innovation Management (ISPIM).
Volunteer
Engineering and Computer Science Graduate Poster Competition
March 2020
Carleton University
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