Senior Data Scientist
2025-11-17T06:00:02+00:00
Private Company
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https://www.greatkenyanjobs.com/employers/company-detail/company-Private-Company-8175/nav-42
FULL_TIME
Nairobi
Nairobi
00100
Kenya
Consulting
Management, Computer, Business Operations
2025-11-19T17:00:00+00:00
Kenya
8
KEY DUTIES
AI and Data Science Leadership: Own the end-to-end lifecycle of AI/ML projects,from ideation and business scoping to prototyping,model packaging and deployment with DevOps, ensuring seamless integration into production environments.
Predictive Analytics and Model Ownership:Own and enhance critical ML
models by continuously monitoring performance, ensuring high accuracy, and implementing improvements to boost predictive power and reliability.
Champion AI-Led Self-Service Data Platform: Spearhead the development
and adoption of an AI-driven self-service data platform,leveraging generative AI,AI agents, and LLMs to automate tasks,treamline workflows, and empower teams.
Drive Innovation through POCs: Proactively design and execute POCs using AI to test hypotheses, validate business use cases, and develop new models to address user needs or simplify processes through automation,collaborating with the Head of Data to align with strategic goals.
Business Process Optimization: Partner with business teams (via the Data
Business Partner) to identify repetitive, decision-heavy, or complex tasks,applying predictive models or AI-driven automation to optimize processes and deliver measurable value.
MLOps and AI Governance: Collaborate with Data Engineers and DevOps to build robust ML pipelines, ensuring model monitoring, versioning, and reliaility. Maintain AI fairness, performance, and compliance, particularly for region-specific use cases like credit scoring or customer segmentation, adhering to local regulations.
Cross-Functional Collaboration: Work with department heads and stakeholders to understand challenges and align AI-driven solutions with strategic objectives, fostering trust through clear communication and impactful deliverables.
Continuous Improvement: Driven by curiosity and innovation, identify and implement enhancements to data science processes, model accuracy, and analytics workflows. Take ownership of initiatives, ensuring follow-through to completion and delivering solutions that enhance efficiency and data trust
AI and Data Science Leadership: Own the end-to-end lifecycle of AI/ML projects,from ideation and business scoping to prototyping,model packaging and deployment with DevOps, ensuring seamless integration into production environments. Predictive Analytics and Model Ownership:Own and enhance critical ML models by continuously monitoring performance, ensuring high accuracy, and implementing improvements to boost predictive power and reliability. Champion AI-Led Self-Service Data Platform: Spearhead the development and adoption of an AI-driven self-service data platform,leveraging generative AI,AI agents, and LLMs to automate tasks,treamline workflows, and empower teams. Drive Innovation through POCs: Proactively design and execute POCs using AI to test hypotheses, validate business use cases, and develop new models to address user needs or simplify processes through automation,collaborating with the Head of Data to align with strategic goals. Business Process Optimization: Partner with business teams (via the Data Business Partner) to identify repetitive, decision-heavy, or complex tasks,applying predictive models or AI-driven automation to optimize processes and deliver measurable value. MLOps and AI Governance: Collaborate with Data Engineers and DevOps to build robust ML pipelines, ensuring model monitoring, versioning, and reliaility. Maintain AI fairness, performance, and compliance, particularly for region-specific use cases like credit scoring or customer segmentation, adhering to local regulations. Cross-Functional Collaboration: Work with department heads and stakeholders to understand challenges and align AI-driven solutions with strategic objectives, fostering trust through clear communication and impactful deliverables. Continuous Improvement: Driven by curiosity and innovation, identify and implement enhancements to data science processes, model accuracy, and analytics workflows. Take ownership of initiatives, ensuring follow-through to completion and delivering solutions that enhance efficiency and data trust
Demonstrated expertise in designing, prototyping, and deploying machine learning models, including generative AI applications and critical models like Credit Scoring. 🖊 Strong interpersonal and communication skills, with the ability to translate complex AI solutions into clear business value for non-technical stakeholders.
BSc degree in Computer Science, Statistics, Applied Mathematics, Engineering or a related field. Minimum of 5 years of hands-on experience developing and deploying data science or AI/ML solutions in a business setting, with a proven track record in AI strategy and implementation
JOB-691ab9e28a43a
Vacancy title:
Senior Data Scientist
[Type: FULL_TIME, Industry: Consulting, Category: Management, Computer, Business Operations]
Jobs at:
Private Company
Deadline of this Job:
Wednesday, November 19 2025
Duty Station:
Nairobi | Nairobi | Kenya
Summary
Date Posted: Monday, November 17 2025, Base Salary: Not Disclosed
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JOB DETAILS:
KEY DUTIES
AI and Data Science Leadership: Own the end-to-end lifecycle of AI/ML projects,from ideation and business scoping to prototyping,model packaging and deployment with DevOps, ensuring seamless integration into production environments.
Predictive Analytics and Model Ownership:Own and enhance critical ML
models by continuously monitoring performance, ensuring high accuracy, and implementing improvements to boost predictive power and reliability.
Champion AI-Led Self-Service Data Platform: Spearhead the development
and adoption of an AI-driven self-service data platform,leveraging generative AI,AI agents, and LLMs to automate tasks,treamline workflows, and empower teams.
Drive Innovation through POCs: Proactively design and execute POCs using AI to test hypotheses, validate business use cases, and develop new models to address user needs or simplify processes through automation,collaborating with the Head of Data to align with strategic goals.
Business Process Optimization: Partner with business teams (via the Data
Business Partner) to identify repetitive, decision-heavy, or complex tasks,applying predictive models or AI-driven automation to optimize processes and deliver measurable value.
MLOps and AI Governance: Collaborate with Data Engineers and DevOps to build robust ML pipelines, ensuring model monitoring, versioning, and reliaility. Maintain AI fairness, performance, and compliance, particularly for region-specific use cases like credit scoring or customer segmentation, adhering to local regulations.
Cross-Functional Collaboration: Work with department heads and stakeholders to understand challenges and align AI-driven solutions with strategic objectives, fostering trust through clear communication and impactful deliverables.
Continuous Improvement: Driven by curiosity and innovation, identify and implement enhancements to data science processes, model accuracy, and analytics workflows. Take ownership of initiatives, ensuring follow-through to completion and delivering solutions that enhance efficiency and data trust
Work Hours: 8
Experience in Months: 60
Level of Education: professional certificate
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subject 'Senior Data Scientist' not later than 19th November 2025.
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