Data Scientist
2025-04-16T13:03:57+00:00
Kasha Kenya
https://greatkenyanjobs.com/jsjobsdata/data/employer/comp_6853/logo/kasha.png
https://kasha.co.ke/
FULL_TIME
Nairobi
Nairobi
00100
Kenya
Business Management and Administration
Admin & Office
2025-05-06T17:00:00+00:00
Kenya
8
Kasha is a fast-growing startup e-commerce company in East Africa focused on women’s health and personal care, selling products such as menstrual care, contraceptives, HIV self-tests, soaps, lotions, baby diapers, and beauty products. Kasha’s e-commerce is highly accessible across the region and customers can order via website, app, USSD (basic mobile phone, no internet), call center or social media. On top of the consumer business, Kasha’s business includes market insight, analytics, and service offerings to global manufacturers of FMCG, Pharma and Beauty products with the aim of helping them drive their revenue and market penetration.
Lake Nakuru birdwatching tours
Online training courses
Data Scientist
About the Role
The Data Scientist will leverage AI/ML-driven predictive analytics to support the development and deployment of Proof-of-Concept (PoC) and Minimum Viable Products (MVPs) focused on NCD (Non-Communicable Diseases) patient retention, delivery forecasting, behavioral adherence, and AI-powered virtual assistants. The role involves building machine learning models for risk scoring, adherence prediction, and supply chain optimization while integrating insights into existing healthcare and logistics dashboards to improve patient outcomes and operational efficiency. Role can be based in Egypt, Rwanda, Kenya and/or South Africa.
Responsibilities
- Predictive Analytics & AI Models
- Design and develop AI-driven risk scoring models to identify NCD patients at risk of disengagement.
- Build predictive models to forecast eligibility transitions for improved patient care pathways.
- Implement a Machine Learning-based adherence segmentation model to analyze patient behavior patterns.
Delivery Forecasting & Supply Chain Optimization
- Develop an AI-powered delivery forecasting model to predict medication delivery accuracy and potential delays.
- Integrate predictive insights into logistics and warehouse management systems to improve proactive planning.
Lake Nakuru birdwatching tours
- AI-Powered Virtual Assistants
- Develop and deploy AI-powered chatbots and virtual assistants for medication reminders, real-time patient engagement, and adherence support.
- Enable self-service patient platforms for medication-related queries and preference management.
Data Engineering & Infrastructure
- Design and optimize Python-based ETL pipelines for data flow between AI models and healthcare dashboards.
- Work with MS Dynamics integrations to enhance AI-driven decision-making in clinical and operational processes.
- Ensure seamless API integrations for real-time data exchange between predictive models and user-facing applications.
Monitoring, Validation & Deployment
- Develop real-time monitoring mechanisms for risk stratification insights and adherence dashboards.
- Optimize CI/CD pipelines for AI/ML model deployment and automate API-based data updates.
- Conduct model validation, A/B testing, and performance tuning to refine PoC models before MVP scaling.
Collaboration & Knowledge Sharing
- Work closely with healthcare professionals, supply chain teams, and DevOps engineers to align AI models with operational needs.
- Provide executive-level data insights through Jupyter notebooks and visualization dashboards.
- Contribute to AI/ML best practices through code reviews, documentation, and team knowledge sharing.
Qualifications
- Machine Learning & AI: Supervised and unsupervised learning, risk prediction models, forecasting algorithms.
- Programming & Data Processing: Python, SQL, Pandas, Scikit-learn, TensorFlow/PyTorch.
- Cloud & Infrastructure: AWS (RDS, Lambda, SageMaker), Google Cloud, or Azure AI services.
- ETL & Data Engineering: Experience with building scalable data pipelines for ML models.
- APIs & Integration: REST APIs, MS Dynamics API, healthcare data interoperability.
- Visualization: Jupyter, Power BI, or similar platforms.
Experience
- 3+ years of experience in Data Science, AI/ML, or predictive analytics in healthcare, logistics, or enterprise AI applications.
- Microsoft Data Analyst Associate certification or BSc in Computer Science, AI, or a related field.
Knowledge
- Strong communication skills for engaging clinical teams, engineers, and business stakeholders.
- Ability to translate complex AI insights into actionable business strategies.
- Experience in healthcare analytics, supply chain optimization, or chatbot development is a plus.
Predictive Analytics & AI Models Design and develop AI-driven risk scoring models to identify NCD patients at risk of disengagement. Build predictive models to forecast eligibility transitions for improved patient care pathways. Implement a Machine Learning-based adherence segmentation model to analyze patient behavior patterns. Delivery Forecasting & Supply Chain Optimization Develop an AI-powered delivery forecasting model to predict medication delivery accuracy and potential delays. Integrate predictive insights into logistics and warehouse management systems to improve proactive planning. Lake Nakuru birdwatching tours AI-Powered Virtual Assistants Develop and deploy AI-powered chatbots and virtual assistants for medication reminders, real-time patient engagement, and adherence support. Enable self-service patient platforms for medication-related queries and preference management. Data Engineering & Infrastructure Design and optimize Python-based ETL pipelines for data flow between AI models and healthcare dashboards. Work with MS Dynamics integrations to enhance AI-driven decision-making in clinical and operational processes. Ensure seamless API integrations for real-time data exchange between predictive models and user-facing applications. Monitoring, Validation & Deployment Develop real-time monitoring mechanisms for risk stratification insights and adherence dashboards. Optimize CI/CD pipelines for AI/ML model deployment and automate API-based data updates. Conduct model validation, A/B testing, and performance tuning to refine PoC models before MVP scaling. Collaboration & Knowledge Sharing Work closely with healthcare professionals, supply chain teams, and DevOps engineers to align AI models with operational needs. Provide executive-level data insights through Jupyter notebooks and visualization dashboards. Contribute to AI/ML best practices through code reviews, documentation, and team knowledge sharing.
Machine Learning & AI: Supervised and unsupervised learning, risk prediction models, forecasting algorithms. Programming & Data Processing: Python, SQL, Pandas, Scikit-learn, TensorFlow/PyTorch. Cloud & Infrastructure: AWS (RDS, Lambda, SageMaker), Google Cloud, or Azure AI services. ETL & Data Engineering: Experience with building scalable data pipelines for ML models. APIs & Integration: REST APIs, MS Dynamics API, healthcare data interoperability. Visualization: Jupyter, Power BI, or similar platforms.
JOB-67ffaabd6a4d2
Vacancy title:
Data Scientist
[Type: FULL_TIME, Industry: Business Management and Administration, Category: Admin & Office]
Jobs at:
Kasha Kenya
Deadline of this Job:
Tuesday, May 6 2025
Duty Station:
Nairobi | Nairobi | Kenya
Summary
Date Posted: Wednesday, April 16 2025, Base Salary: Not Disclosed
Similar Jobs in Kenya
Learn more about Kasha Kenya
Kasha Kenya jobs in Kenya
JOB DETAILS:
Kasha is a fast-growing startup e-commerce company in East Africa focused on women’s health and personal care, selling products such as menstrual care, contraceptives, HIV self-tests, soaps, lotions, baby diapers, and beauty products. Kasha’s e-commerce is highly accessible across the region and customers can order via website, app, USSD (basic mobile phone, no internet), call center or social media. On top of the consumer business, Kasha’s business includes market insight, analytics, and service offerings to global manufacturers of FMCG, Pharma and Beauty products with the aim of helping them drive their revenue and market penetration.
Lake Nakuru birdwatching tours
Online training courses
Data Scientist
About the Role
The Data Scientist will leverage AI/ML-driven predictive analytics to support the development and deployment of Proof-of-Concept (PoC) and Minimum Viable Products (MVPs) focused on NCD (Non-Communicable Diseases) patient retention, delivery forecasting, behavioral adherence, and AI-powered virtual assistants. The role involves building machine learning models for risk scoring, adherence prediction, and supply chain optimization while integrating insights into existing healthcare and logistics dashboards to improve patient outcomes and operational efficiency. Role can be based in Egypt, Rwanda, Kenya and/or South Africa.
Responsibilities
- Predictive Analytics & AI Models
- Design and develop AI-driven risk scoring models to identify NCD patients at risk of disengagement.
- Build predictive models to forecast eligibility transitions for improved patient care pathways.
- Implement a Machine Learning-based adherence segmentation model to analyze patient behavior patterns.
Delivery Forecasting & Supply Chain Optimization
- Develop an AI-powered delivery forecasting model to predict medication delivery accuracy and potential delays.
- Integrate predictive insights into logistics and warehouse management systems to improve proactive planning.
Lake Nakuru birdwatching tours
- AI-Powered Virtual Assistants
- Develop and deploy AI-powered chatbots and virtual assistants for medication reminders, real-time patient engagement, and adherence support.
- Enable self-service patient platforms for medication-related queries and preference management.
Data Engineering & Infrastructure
- Design and optimize Python-based ETL pipelines for data flow between AI models and healthcare dashboards.
- Work with MS Dynamics integrations to enhance AI-driven decision-making in clinical and operational processes.
- Ensure seamless API integrations for real-time data exchange between predictive models and user-facing applications.
Monitoring, Validation & Deployment
- Develop real-time monitoring mechanisms for risk stratification insights and adherence dashboards.
- Optimize CI/CD pipelines for AI/ML model deployment and automate API-based data updates.
- Conduct model validation, A/B testing, and performance tuning to refine PoC models before MVP scaling.
Collaboration & Knowledge Sharing
- Work closely with healthcare professionals, supply chain teams, and DevOps engineers to align AI models with operational needs.
- Provide executive-level data insights through Jupyter notebooks and visualization dashboards.
- Contribute to AI/ML best practices through code reviews, documentation, and team knowledge sharing.
Qualifications
- Machine Learning & AI: Supervised and unsupervised learning, risk prediction models, forecasting algorithms.
- Programming & Data Processing: Python, SQL, Pandas, Scikit-learn, TensorFlow/PyTorch.
- Cloud & Infrastructure: AWS (RDS, Lambda, SageMaker), Google Cloud, or Azure AI services.
- ETL & Data Engineering: Experience with building scalable data pipelines for ML models.
- APIs & Integration: REST APIs, MS Dynamics API, healthcare data interoperability.
- Visualization: Jupyter, Power BI, or similar platforms.
Experience
- 3+ years of experience in Data Science, AI/ML, or predictive analytics in healthcare, logistics, or enterprise AI applications.
- Microsoft Data Analyst Associate certification or BSc in Computer Science, AI, or a related field.
Knowledge
- Strong communication skills for engaging clinical teams, engineers, and business stakeholders.
- Ability to translate complex AI insights into actionable business strategies.
- Experience in healthcare analytics, supply chain optimization, or chatbot development is a plus.
Work Hours: 8
Experience in Months: 36
Level of Education: bachelor degree
Job application procedure
Submit your CV and Application on Company Website : Click Here
All Jobs | QUICK ALERT SUBSCRIPTION
