Job Description

The Senior Data Scientist is both a strategic and hands-on role, focusing on advancing our data science roadmap, building smart and scalable products, and elevating the department’s machine learning maturity. The successful candidate will bring a blend of technical excellence, visionary thinking, and strong leadership to shape how Venn uses data to predict, inform, and deliver meaningful outcomes. The role requires a deep understanding of statistical modeling, machine learning algorithms, and data science methodologies to provide actionable insights and improve overall efficiency.

Roles & Responsibilities

Strategic AI & ML Leadership 

• Champion the organisation’s AI and ML strategy, aligning technical capabilities with organisational goals and impact metrics.
• Lead the development of flagship AI solutions such as climate risk engines, household vulnerability scoring, crop diagnostics, and more.
• Foster a roadmap of experimentation and continuous learning, including internal pilots and partnerships with research and academic institutions. 

Technical Oversight & Model Development 

• Lead end-to-end development of robust machine learning models — from data discovery and feature engineering to deployment and monitoring.
• Build models that go beyond outputs to predict outcomes, evaluate counterfactuals, and support early warning systems like risk assessments.
• Ensure all models are explainable, ethical, and responsive to field realities in low-data environments.

Team Leadership & Mentorship 

• Supervise and mentor a cross-functional team of data scientists, ML engineers, and data engineers.
• Cultivate a strong culture of collaboration, technical growth, and continuous innovation.
• Guide peer learning and internal capacity building across Venn and program teams. 

Product Integration & Scale 

• Work with product managers, software engineers, and other teams to integrate AI/ML features into digital platforms used by field teams.
• Support the development of real-time analytics tools and advisory systems that are accessible, reliable, and actionable at the last mile. 

Innovation Partnerships & Influence 

• Represent Venn’s AI capabilities internally and externally to build visibility and partnerships that enhance our innovation portfolio.
• Stay ahead of emerging trends in AI, ML, and data science and translate relevant advances into RTV’s context.

Requirements and Experience

Qualifications and Skills 

• Bachelor’s degree in Data Science, Computer Science, Statistics, Artificial Intelligence, Mathematics, Economics, or a related field.
• At least 4 years of experience in predictive analytics, AI, machine learning, or data science.
• Strong proficiency in programming languages such as Python, R, SQL, or Julia.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and big data technologies.
• Expertise in statistical analysis, predictive modeling, and algorithm development.
• Proficiency in data visualization tools such as Tableau, Power BI, or Matplotlib.
• Knowledge of cloud-based AI services (e.g., AWS, Google AI, Azure Machine Learning)
• Strong problem-solving and critical-thinking skills with a results-oriented approach.
• Excellent communication and collaboration skills to work effectively with diverse teams.
• Ability to manage multiple projects and adapt to evolving priorities.
• Experience in applied AI within social impact, healthcare, or rural development contexts is desirable. 

Personal Qualities: 

• Highly motivated and proactive with a passion for data-driven innovation.
• Strong analytical mindset with attention to detail.
• Ability to work independently and collaboratively in a fast-paced environment.
• Enthusiastic about applying AI and predictive analytics for social good.
• Commitment to diversity, equity, and inclusion in workplace practices.

Application Process

To apply, please submit your application here.

Raising The Village is an equal-opportunity employer committed to diversity and inclusion. We highly encourage women candidates to apply.

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