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Skills

  • Attendance tracking
  • Team building
  • Process improvement
  • Feature engineering and selection
  • Collaboration with Multidisciplinary Teams
  • Supervision
  • Insurance billing
  • Advanced Excel for data analysis
  • Group instruction
  • Python programming

Work Experiences

  • Awarded in Employee of the Year.
  • Completed risk assessment research as part of a 7-person graduate team.
  • Assisted in grading.
  • Addressed student challenges in data wrangling techniques.
  • 5 projects received recognition.
  • Developed a reputation for punctuality and hard work.
  • Assisted with resume building and interview preparation.
  • Assisted with troubleshooting complex data science issues for textbooks and coursework, reducing student query response times by 37% minutes.
  • Kept my program knowledge up to date by doing performance reporting and cross-functional collaboration.
  • Analyzed student performance data to identify areas of improvement, resulting in a restructured curriculum that improved outcomes by 71%.

Summaries

  • Able to translate complex information into simple terms.
  • Results-oriented Miscellaneous professional with risk assessment, process improvement, and risk assessment strengths.
  • Initiative, process, and framework are all available.
  • Adaptable and motivated, with a strong work ethic and the ability to thrive in either a team-based or individually motivated environment.
  • Achieved a 72% rise in course-wide success rates.
  • Data Science Teaching Assistant is a dedicated Data Science Teaching Assistant who specializes in leading courses in a decisive and focused manner.
  • Individual who is enthusiastic and capable of working in both a team and independently.
  • Achieved 77% proficiency among participants.
  • Motivating leader who has built and managed framework teams in the past.
  • Achieved a 37% improvement in coding quality.

Accomplishments

  • Created Python-based coding exercises on K-means clustering to help students grasp complex machine learning concepts, directly boosting exam scores by 52%.
  • Implemented a peer review process for student projects, encouraging collaboration and improving the quality of end projects by 24% points.
  • Designed practical coding challenges using real-world scenarios, leading 40% of students to successfully complete their assignments ahead of the deadline.
  • Led coding workshops focusing on data wrangling techniques, which resulted in 41% of students completing exercises with fewer errors.
  • Supervised and graded final student projects focused on real-time data streaming, with 46% attaining high distinctions or industry recognition.
  • Developed supplementary material explaining the ETL process, which helped students comprehend data handling and transformation by increasing performance by 54%.
  • Worked with instructors to standardize grading rubrics, reducing time spent grading by 57% without sacrificing feedback quality.
  • Developed interactive Jupyter Notebook labs focused on supervised learning techniques, increasing student interaction with course material by 37%.
  • Organized small group sessions focused on debugging and optimizing code practices, reducing error rates in student submissions by 37%.
  • Collaborated with senior faculty to manage course structure and ensure alignment with the latest industry trends, leading to 19% positive feedback from students.

Affiliations

  • Graduate Research Assistant, category Department of Computer Science, 2023–2020
  • Participating Member, Global AI and Data Science Online Communities, 2020–Present
  • Member, Women in Data Science (WiDS), 2023–Present
  • Attendee, PyData Conference, 2023
  • Recipient, program for Machine Learning Research at framework, 2019
  • Contributor, Open-Source Data Science Projects on GitHub, 2015–Present
  • Member, Data Science Association (DSA), 2023–Present
  • Volunteer Instructor, Data Science for Social Good (DSSG) Seattle, 2023
  • Attendee, Strata Data Conference, 2023
  • Member, Python Software Foundation (PSF) 2024-Present

Certifications

  • Microsoft Certified Systems Engineer (MCSE)
  • Certified Artificial Intelligence Engineer - Meridian
  • Google Professional Machine Learning Engineer
  • Master's Degree in Data Science – system
  • Cisco Certified Internetwork Expert (CCIE)
  • Data Visualization with Python Certification - Summit Group
  • Cisco Certified Network Associate (CCNA)
  • Google Educator Level 1 & 2 Certifications (for teaching-related roles)
  • Introduction to Statistics & Data Science Certificate – Ironclad Systems
  • CompTIA Security+

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