Data Science Power Bi

NASIM ESHGARF

LinkedIn ad7kgh@r.postjobfree.com 651-***-**** Minneapols,MN

SUMMARY

With dual master's degrees in Educational Psychology and Computer Science, I blend deep expertise in data science, including machine learning, deep learning, and business analytics, with innovative evaluation methods for AI systems using both qualitative and quantitative psychological measures. My proficiency in Python, R, SQL, and data visualization tools like Power BI and my research on the interplay between video gaming and learning showcases my unique skill set. Focused on data science roles, I apply a comprehensive, mixed-methods approach to enhance AI evaluation and data analysis, positioning me uniquely in the field. EDUCATION

University of Minnesota – Twin Cities, Minneapolis, MN, USA 09/2022 – Present M.S. in Computer Science program

M.A. in Psychological Foundations of Education program University of Tehran, Tehran, Iran 09/2014 – 02/2017 M.Sc. in IT Management

Thesis: A motivation-based clustering of Iranian Facebook users Awards: Graduate Student Fellowship

University of Shahr-e-Kord, Chaharmahal and Bakhtiari, Iran 09/2004 – 09/2010 B.Sc. in IT Engineering

Awards: Full-Tuition Scholarship

WORK EXPERIENCE

Research Assistant in Minnesota Child Welfare Training Academy 08/2023 - present I gather and organize extensive datasets from various sources, like Qualtrics, to maintain data integrity and accessibility. My work involves applying advanced analytical techniques to qualitative and quantitative research, deriving insights that shape child welfare strategies. I create intuitive dashboards and detailed reports in Power BI, making complex data sets accessible and actionable through visual representation.

Data Analytics intern in Minnesota Orchestra 05/2023 - 08/2023 I cleaned and analyzed complex datasets for strategic decision-making, utilizing SQL for database management. My creation of Power BI dashboards allowed for real-time data insights, improving interpretability for teams. Leading projects across departments, we developed specialized dashboards for marketing and HR, enhancing strategy optimization and decision-making. We predicted marketing strategies using post-concert data and presented these predictions to the marketing team, further informing their strategic planning and performance enhancement efforts. Teaching Assistant in Basic and Applied Statistics, University of Minnesota 01/2023 - 05/2023 Teaching Assistant in Psychological Science Applied, University of Minnesota 08/2022 - 05/2023 Research assistant at Carlson School of Management, University of Minnesota 08/2021-06/2022 I played a key role in sourcing and managing large datasets from the Open FDA’s API, showcasing my ability to navigate large-scale data operations efficiently. I identified critical patterns and insights through detailed exploratory analysis, guiding further research directions. Employing advanced statistical methods and analytics tools, I conducted predictive analyses that were pivotal in understanding data trends and forecasting future outcomes. My comprehensive support in data analysis significantly boosted the research team's efforts, enhancing the quality and impact of our projects.

Teaching Computational Thinking to Elementary Students 2017 to 2020 Data analysis in Kayson 09/2015 - 06/2018

Researcher in Iran Telecommunication Research Center 01/2015 - 08/2015 Product Manager in Barfab 04/2011 - 08/2014

Volunteer Work Experience:

● Member of the activity board of the CSCC since June 2020.

● Volunteer in Imam Ali Popular Students Relief Society from 2010 to 2018.

● Volunteer in Safa Organization (helping children with cancer) from 2013 to 2015 SKILLS

Technical: Python (TensorFlow, Keras, NumPy, Pandas), C++, R, SQL, HTML, CSS, Power BI, Tableau, Figma

Analytics: Machine Learning, Deep Learning, Hypothesis Testing, Experiments GRADUATE COURSES

Machine Learning Fundamentals, Deep Learning, Data Mining, Statistical Analysis, Business Intelligence, Organizational Behavior, Database Management Systems, Computer Vision

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