About

I am a self-motivated, determined, confident, result oriented and hardworking individual with an adaptable approach to work. I possess strong communication and interpersonal skills and I am an exquisite innovative team player with a complimentary knack of working on my own initiative and under minimum supervision. I have the ability to organize and prioritize assigned tasks effectively. I also have the ability to observe ethical standards and work well with colleagues and keep time.

Skills

  • Data Analysis
    8
  • Python
    8
  • Git and Github
    8
  • R
    8
  • EXCEL
    8
  • English
    9
  • Swahili
    9

Experience

wanjiru kinyara

Work experience
  • September, 2023 - April, 2024
  • Fulltime
  • Analyzed daily productivity reports, including damages and rejections, to identify trends and areas for improvement in workshop operations.
  • Prepared workshop reports highlighting productivity metrics and providing insights for management decision-making.
  • Managed the damages report, tracking and analyzing damages occurring in the workshop to identify root causes and implement corrective actions.
  • Oversaw branches in Rwanda and Uganda, ensuring data integrity and consistency in reporting across locations.
  • Implemented measures to prevent the resend of certain lenses' orders back to Kenya, optimizing supply chain efficiency and reducing costs.
  • Collaborated with stakeholders to develop and implement data-driven strategies to enhance workshop efficiency and reduce damages.
  • Utilized statistical techniques and predictive modeling to forecast damages and identify proactive solutions.
  • Prepared and presented reports and visualizations to communicate findings and recommendations to stakeholders.
  • Automated a report to send emails to branches for warrant returns on orders that are a couple of days old or older.

wanjiru kinyara

Education
  • February, 2021 - August, 2021
  • Fulltime
  • Programming Languages:
  • Python, R, SQL
  • Data Manipulation and Cleaning:
  • Pandas, dplyr, NumPy
  • Statistical Analysis:
  • Understanding of basic statistics, Hypothesis testing, regression analysis, and ANOVA.
  • Machine Learning:
  • 1. Supervised and unsupervised learning algorithms (e.g., linear regression, logistic regression, decision trees, clustering, etc.)
  • 2. Libraries such as scikit-learn, TensorFlow, and Keras.
  • Data Visualization:
  • Matplotlib and Seaborn, ggplot2 (R), Tableau and Power BI
  • Analytical Skills:
  • Critical Thinking, Problem Solving, Domain Knowledge,
  • Communication, Curiosity, Attention to Detail, Collaboration, Adaptability.
  • Tools and Technologies:
  • Jupyter Notebook, RStudio, PyCharm, Git, Tableau and Power BI, GitHub, JIRA

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