SUMMARY:

• 7 + years of experience as a data analyst, 3+ years of experience as a data scientist.
• Experienced in data cleaning, missing values handling, reshaping, and exploratory analysis (EDA)with advanced data mining and Natural Language Processing(NLP) techniques.
• Experienced in using Python analysis tools - (Pandas, Numpy, Matplotlib, SeaBorn, Bokeh, Tableau, Sci-kit, NumPy, SciPy, NLTK, XgBoost, CatBoost and Genetic Algorithms).
• Proficient with supervised and unsupervised learning.
• Performed predictive analysis with linear, polynomial, logistic regression and SVM.
• Utilized K-means and Classification Trees for clustering.
• Proficient to handle bias (under fitting) and high variance (over fitting).
• Experienced in data acquisition with MS SQL Server, MySQL, PostgreSQL and SQL. Creating, configuring and reshaping tables using advanced SQL queries + in data scraping with Selenium, BeautifulSoup, Requests, Urllib, HTML, API.
• Able to access data through API/RESTful services.
• Experienced in preparing and presenting daily, weekly and monthly and on-demand reports.
• Ability to handle multiple tasks and responsibilities independently as well as a proactive team member/leader.
• Developed hypothesis statements and applied statistical testing.

SKILLS:

Programming: Python, SQL, Apache Spark (Python, Scala(Beginner)

Tools: Numpy, Pandas, Matplotlib, Seaborn, Bokeh, Tableau, SciPy, Sci - kit, Stats Model, NLTK, TPOT, H2O, AutoML, SQL Alchemy, PostgreSQL, NO-SQL, Hadoop, AWS EC2, Google Colab, XgBoost, CatBoost, Flask.

WORK EXPERIENCE:

Data Scientist/Consultant

Confidential, Austin, TX

Responsibilities:

• Scraped Data from Web provider, Developed Exploratory Data Analysis and Contemporary Machine
• Learning Models and deployed them to provide industrial solutions at marketing.
• Implemented projects in Python by using linear regression, logistic regression, supervised learning and Natural Language
• Processing and other advance data analysis techniques such as clustering, principle component analysis, spatial analysis, etc.

Maritime Data Analyst

Confidential

Responsibilities:

• Analyzed all dimensions of Operational Area for Confidential Operations in Afghanistan and optimized %80 of the planning data for the planning staff.
• Contributed to the planning team as syndicate leader and data analyst, participated in every level meeting, prepared and presented on-demand reports (Best Course of Actions) to the decision makers to ensure appropriate measures to be taken.
• Analyzed the options (multi criteria decision optimization etc.) of Confidential initiatives for the North African Countries, ended up with creation of Expeditionary Training Teams for North African Countries Confidential Forces to enhance the Security in Mediterranean Sea.

Confidential

Operations Research Analyst /Modelling and Simulation Engineer

Responsibilities:

• Assumed roles at different stages such as Chief Planning Confidential Officer, Modelling and Simulation Software Engineer, Operations Research Analyst. Contributed to the Battle Readiness Evaluation System by creating a new reporting mechanism for each platform.
• Assumed plentiful projects in relation with Data Analysis, Optimization and Simulation & Modelling.
• Established a new approach of Operations/Training Assessment and Evaluation system for Confidential Forces to analyze more than 100 warships operations/training cycle and committed increasing effectiveness of Confidential
• Used geo-spatial data to visualize war ships’ sail patterns to extend the radar/sonar coverage.
• Through data analysis and optimization techniques, helped decision makers overcome complicated problems.
• Prepared and presented, monthly, bi-annually, annually and on-demand reports to the decision makers.