Daniel Zhou
Data Analyst @Possibility Labs
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WORK HISTORY
Data Analyst @Possibility Labs
San Francisco, CA, US
Facilitated the disbursement of over $30MM to 200+ client accounts by developing an innovative capital movement workflow automation using Power Automate and custom Python scripts Created dynamic ad-hoc reports that not only track client donations but also provide detailed insights of societal impacts by analyzing geographic regions, target populations, and problem issues, further highlighting the valuable contributions made through these donations Demonstrated innovation and leadership by leveraging Node JS, Python, and Power Automate to develop an automated process that seamlessly connects bank accounts with internal systems, enabling customers to effortlessly take ownership of banking data Exhibited creative problem-solving skills and mastery of Salesforce in designing a client facing portal providing for a seamless UI/UX, and configuring the Salesforce instance to automate processes and store data as part of a grants management system
EDUCATION
Purdue University
Bachelor of Science (B.S.), Aerospace Engineering
Iowa State University
Master of Science (M.S.), Aerospace, Aeronautical and Astronautical Engineering
SKILLS
ABOUT DANIEL ZHOU
Results-oriented Data Analyst with 7 years of experience and a strong track record of developing innovative solutions and driving cost savings. Expertise in data science, artificial intelligence (AI), finance and operations, process automation, systems integration and research. Seeking opportunities to apply my skills and contribute to the success of a forward-thinking organization.Programming Languages: SQL, Python, JavaScript, C, VBA, MATLABTools: Tableau, Power BI, Power Automate, Oracle, SQL Server, Azure, Salesforce, Zendesk, ServiceNow, JD EdwardsFrameworks: pandas, NumPy, Node JS, Express JS, TensorFlow, Keras, scikit-learn, Matplotlib, SeleniumSpecialties: Business Intelligence (BI), Data Analysis, Data Warehousing, Data Visualization, Data Extract Transform Load (ETL), Machine Learning (ML), Financial and Demand Planning, Data Mining, Big Data, Robotic Process Automation (RPA), Natural Language Processing (NLP), User Experience (UX)
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