Judy Ngethe

• Vision and Strategy
  
• Product Development
• Business Development
• Sales and Marketing
• Financial Management
• Operations and Infrastructure
• Customer Relations
• Research and Development
  
  
  
  
  
  
  
  
  

• Brand Development
• Product Development
• Sales and Distribution
• Marketing and Promotion
• Customer Relations
• Supply Chain Management
• Quality Control and Compliance
• Financial Management
• Research and Development
• Sustainability and Ethical Practices
  
  
  
  
  
  
  
  
  
  

Strategically minded junior data analyst with a BSC in Applied Computing from Kcau (Second Upper) with a strong background in Excel and Statistics, BI tools, Python, Numpy, Pandas, Data Visualization Libraries, SQL &MongoDB, and Soft Skills. Eager to develop new business solutions.

TECHNICAL SKILLS

Analytical Tools: Tableau, SAS EM, Power BI, SAP Business Objects, Crystal Reports,SAP Lumira, Advance Excel.

Tools: Numpy, Pandas, Matplotolib, Scipy, Skit learn, Machine Learning, Deep Learning, Keras TensorFlow. Artificial Neural Network JIRA, Kanban board

Software: JUPYTER N/B, Spyder, R, Ms. Exel, Mysql

Programming Languages: SQL, HTML, CSS, PYTHON, JAVASCRIPT ,

jquery, NODE.JS,REACT.JS ,R,C++

Database: Big Data Environment – Microsoft SQL Server, RDBMS

ACADEMIC PROJECTS

Predicting student performance Jan -March 2021

Predictive_learner_analytic_system: https://github.com/claire-sivan/Predictive_learner_analytic_system

Pharmaceticual_web_based_app : https://github.com/claire-sivan/phamaceticual_web_based_app May-Aug 2021

• front end: UI will be in HTML ,CSS, Javascript.
• Back end : Python flask server
• Database:msql

Potato Disease Prediction and Diagnosis App: Sep 221_April 2022

Code:https://github.com/claire-sivan/Potato-Disease-Prediction-and-Diagnosis-App_

• Dataset is taken from Kaggle -https://www.kaggle.com/arjuntejaswl/p..
• Model Building : tensorflow , CNN , data augmentation, tf dataset.
• Backend Server and ML Ops: tf serving , FastAPI.
• Model Optimization:Quantization, Tensorflow lite.
• Frontend:REact Js, React Native.
• Deployment GCP(Google cloud platform ) GCF (Google cloud ).

Learning Red Hat Technologies: Engage in structured training programs to learn about Red Hat Enterprise Linux, including its installation, configuration, and administration. Gain knowledge of essential tools, services, and concepts associated with Red Hat technologies.

• Explain concepts to students and help them solve problems step-by-step.
• Contribute study guides or write new ones
• Help Students Learn. Work with students to provide explanations to help them study and succeed in their courses.

• Training.
• Conducting Interviews.
• Building Rapport.
• Data Accuracy and Completeness.
• Confidentiality and Data Protection.
• Problem Resolution.
• Documentation and Reporting.
• Adhering to Ethical Standards.
  
  
  
  
  
  
  .

• Product Promotion
• Customer Relationship Management
• Sales Planning and Target Setting
• Sales Execution
• Distributor Management
• Market Analysis and Competitor Monitoring
• Trade Shows and Events
• Sales Reporting and Analysis
  
  
  
  
  

• Created and enhanced call sequencing flows and scripts to enhance team performance.
• Monitored and reported on trends in customer interaction to evaluate processes and capitalize on improvement opportunities.
• Resolved concerns with products or services to help with retention and drive sales.
• Implementation of CCFOT project across the business.
• Assisted in the development of CCFOT tool automation and integrated with f-shift to guarantee accurate and consistent data generation Provide education and training for planners, customer development team, warehouse and distribution, and customer service teams on CCFOT project.
• Coordinating four different CCFOT teams in loss identification and reduction.
• Understanding factors that influence organization losses and identity, and business opportunities.
• Circulate weekly customer service reports to the business and monthly reports to the business leadership team.
• Report to the region (Africa) on a monthly and quarterly basis.
• Best Practice in East and Central Africa.
• Developing project reports and presentations covering the following areas.

* Progress

*Activities

*Expectations

*Timeline

• Root Cause analysis on forecast bias accuracy maintained at +-5% for 4 weeks and +-10%for 13 weeks in 13 months.
• Root Cause analysis on output reliability from an average of 50% - 80% in 6 months.
• Clean database on a periodic basis – all products, brands, and categories.
• Review statistical models on a weekly basis.
• Validate forecast in F- shift against Mercia.
• Maintain market groups, for straight packs and promotional packs.