Data Scientist - Senior Associate (Southern Africa) at Genesis Analytics

Requirements

• We're looking for a dynamic and motivated Data Scientist to join our Health Practice. This is an exceptional opportunity to leverage your advanced data science skills and passion for public health to drive impactful projects across Africa. You'll be instrumental in exploring, developing, and implementing innovative data-driven solutions, from strategic data analysis to hands-on model building and deployment.

Key responsibilities:

• Business Development & Opportunity Identification: Actively engage in business development activities, focusing on winning new work both with prospective clients and within existing Health Practice projects, by identifying unmet needs and emerging trends in digital health across Africa. You'll build and nurture relationships with potential clients and partners, translating their challenges into compelling, data-driven solutions and proposals.
• Data-Driven Solution Design & Prototyping: Apply your expertise in data analysis, statistical modeling, and machine learning to understand complex health problems, define data requirements, and rapidly prototype data-driven solutions. This includes designing experiments and evaluating the feasibility of new approaches.
• Machine Learning Model Development & Deployment: Take ownership of the technical aspects of projects, designing, developing, and deploying machine learning models (e.g., predictive analytics, natural language processing, image recognition) to address specific health challenges. This involves supervising rigorous data cleaning, feature engineering, model training, validation, and integration into digital platforms.
• Cross-functional Collaboration & Communication: Collaborate closely with internal and external teams, including health experts, software developers, and clients, translating complex data science concepts and findings into clear, actionable insights that drive project success and inform strategic decision-making.
• Advanced Research & Analysis: Conduct in-depth research on emerging digital health technologies, advanced data science methodologies, and AI trends, providing crucial insights to inform project direction, optimize model performance, and identify new areas for innovation and business growth.

You are likely to have:

• A Master's or Ph.D. degree in a quantitative field such as Computer Science, Data Science, Statistics, Mathematics, Biostatistics, or a related discipline. Your academic foundation provides the rigorous thinking needed to tackle complex, real-world problems.
• Proven experience (Masters + 4 years, or PhD + 3 years) as a Data Scientist in a health setting with a strong portfolio that demonstrates not only your technical prowess but also your ability to translate data-driven insights into compelling business cases and viable product concepts.
• Exceptional Business Acumen and Consultative Selling Skills: You can rapidly understand market needs, identify strategic gaps, and proactively propose data science solutions. You are adept at building trusted relationships with internal and external stakeholders, potential clients, and partners, clearly articulating the commercial value and ROI of analytical solutions.
• Strong coding and modeling expertise in Python and R, including machine learning, deep learning, and statistical modeling libraries. Bonus - You're comfortable with SQL for data manipulation and have experience with cloud platforms (e.g., AWS, Azure, GCP) for scalable solution development and deployment. 
• Demonstrated experience in problem definition and solution design from a commercial perspective. You can translate ambiguous business challenges into clear, data-driven questions and design analytical approaches that lead to actionable and marketable outcomes.
• Excellent communication, presentation, and storytelling skills: You can effectively convey complex technical concepts and analytical findings to diverse audiences, including non-technical business leaders and potential investors, clearly demonstrating the business implications and potential for growth.
• A keen interest in digital health innovation and its application in African contexts, coupled with a passion for identifying and seizing opportunities to leverage data science for social and economic impact.
• Experience with project management methodologies (e.g., Agile), with an emphasis on aligning technical deliverables with business development milestones and commercialization strategies.
• Ability to collaborate effectively with cross-functional teams, including product development, sales, and operations, to ensure that data science initiatives are strategically aligned and contribute directly to business growth.