AI Solutions Lead
Posted:
Company Details
Name:Genesis Analytics
Industry:
Consulting
Website:
http://www.genesis-analytics.com/
Description:
Our purpose is to unlock value in Africa. We use our analytical capabilities to improve decision-making and, through better decisions, to unlock substantial value for our clients and society. While we are the largest economics-based consulting firm in Africa, we use a large number of techniques and …
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Job Details
Job Type:
Full Time
Workplace Type:
On-site
Qualification:
Diploma
Job Experience:
Mandatory
Job Location:
Nairobi County, Kenya
Closing Date:
Undisclosed
Salary:
Undisclosed
Other Pay:
Benefits
Job Category:
Consultancy
Job Description
Key Responsibilities
- Business Origination & Advocacy: Identify "AI-ready" problems within the portfolios of major impact funders. You’ll lead the narrative, helping non-technical stakeholders understand how AI can move the needle on health, education, climate, agriculture, etc.
- Technical Product Ownership: Define the roadmap for AI-driven tools. You will oversee the full lifecycle from discovery and data auditing to deployment and M&E (Monitoring & Evaluation).
- The "Translator" Function: Bridge the gap between data science teams and domain experts. Serve as the vital link between data science teams and domain experts, ensuring that technical complexity never obscures business value.
- Unified Project Orchestration: You serve as the primary bridge between internal teams and external subcontractors, harmonizing disparate workstyles and technical workflows to ensure all contributors are aligned with a single, cohesive strategy.
- Ethical Oversight: Ensure all solutions adhere to Responsible AI principles, specifically focusing on bias mitigation in diverse, non-Western datasets.
Technical Competencies
- To earn the respect of our engineering partners and ensure project success, you should possess:
- ML Literacy: A deep understanding of the Machine Learning lifecycle - from data ingestion and feature engineering to model deployment and drift monitoring.
- Architectural Fluency: Ability to discuss Cloud vs. Edge computing, API integrations, and LLM orchestration (RAG, fine-tuning) with clarity.
- Data Strategy: Expertise in assessing data quality in "noisy" environments. You should know what makes a dataset "fit for purpose" for training.
- Framework Familiarity: High-level understanding of the tech stacks common in the field (e.g., Python, PyTorch/TensorFlow, AWS SageMaker, or Azure ML).
- Business & Strategy Competencies
- Consultative Selling: Proven ability to write winning proposals for multilateral organizations and navigate the procurement nuances of the development sector.
- Strategic Intuition: Ability to distinguish between an "AI hype" project and a sustainable, high-impact solution.
- Stakeholder Management: Experience managing high-level relationships with government officials, NGO directors, and private sector partners.
Experience & Qualifications
- The Background: 6+ years of experience, ideally split between technical product management and strategic consulting/international development.
- The Education: A degree in Computer Science, Data Science, or Engineering is preferred, but an MBA or MPA with a heavy focus on Digital Transformation is also highly valued.
- The "Emerging Market" Edge: Direct experience working in or building tech for Sub-Saharan Africa, Southeast Asia, or Latin America.
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