Organization: Pastel (www.pastel.africa)

Country: USA, Nigeria

Start Date: ASAP

About Us:

At Pastel, we're a dynamic team of designers, builders, and AI experts dedicated to shaping the future of finance and business in Africa. We empower African enterprises with intelligent, AI-driven solutions that streamline operations and drive efficiency. Our mission is to revolutionize finance through cutting-edge technology, making world-class intelligence accessible to businesses across the continent.

Since our launch in September 2021, we've developed tech solutions that help over 120,000 small businesses manage their bookkeeping, generate invoices, and provide receipts. Now, we're expanding our offerings to include financial services, continuing our journey to support small businesses and stimulate economic growth across Africa.

About the Role

As a Data Scientist at Pastel, you will play a pivotal role in shaping the data science strategy that drives our mission of empowering small businesses across Africa. You’ll evaluate existing data science projects, identify optimization opportunities, and implement improvements to deliver cutting-edge AI-driven solutions. In addition, you will design and deploy scalable machine learning systems that solve critical challenges for African businesses. This role offers the chance to make a meaningful impact in the fintech space while working with a dynamic, innovative team.

Key Responsibilities

• Review and refine existing data science projects, models, and workflows to ensure adherence to industry best practices and alignment with business goals.
• Optimize machine learning models and data pipelines for improved performance, accuracy, and scalability.
• Design and deploy robust AI-driven systems and machine learning models to support real-time decision-making and predictive insights for African SMEs.
• Build and maintain data pipelines that handle complex and unstructured datasets for analysis and model training.
• Conduct rigorous testing and statistical analysis to refine and improve model performance using advanced machine learning libraries.
• Lead end-to-end deployment of machine learning models in production environments, collaborating with engineers to ensure stability and real-world applicability.
• Document processes and workflows to ensure clarity, reproducibility, and scalability.
• Mentor junior data scientists, fostering a culture of growth and continuous learning.
• Collaborate with cross-functional teams to elevate the organization’s overall data science capabilities.