Mid/Senior Data Scientist

About Yassir

Yassir is a super app built to simplify everyday life by bringing essential services closer to users through technology and a wide partner network. Its mission is to support people across Africa and the diaspora while also creating economic opportunities for service providers and promoting strong social values. The company is guided by ambition, transparency, trust, quality, and performance, and it is expanding at a very rapid pace.

Joining Yassir means becoming part of one of Africa’s most influential and fastest-growing technology companies.

About the Role

Yassir is looking for a skilled and driven Data Scientist to join its Artificial Intelligence team and help solve high-impact challenges such as dynamic pricing and trip dispatching. In this role, you will analyze data, build models, and improve machine learning systems. A strong mix of predictive modelling ability and software engineering expertise is important, as the work directly supports some of the company’s most critical initiatives.

About the Team

The AI team sits within Yassir’s central Data & AI function, which covers data engineering, data platform management, analytics, AI solutions, and MLOps infrastructure. The team is global, multidisciplinary, and focused on building advanced data and machine learning systems that enable a strong data culture, responsible access to data, informed decision-making, and automation. Team members value curiosity, collaboration, ownership, and meaningful impact.

Key Responsibilities

• Serve as a subject-matter expert for your assigned area and build deep understanding of the underlying business and technical principles.
• Work on high-priority use cases such as pricing optimization, discount and commission strategy, personalized pricing, dispatch optimization, fraud detection, revenue leakage prevention, and recommendations/personalization.
• Spot machine learning opportunities and propose new ideas within your domain and beyond it.
• Help define requirements and priorities for ML initiatives.
• Partner closely with engineering and product stakeholders across functions.
• Promote data quality as a foundational input for analytics and machine learning work.
• Perform exploratory data analysis and develop features through selection and engineering.
• Apply statistical and machine learning methods to train models.
• Test, validate, and fine-tune ML models.
• Present findings and model outcomes using clear visuals and decision-oriented metrics.
• Deploy and evaluate machine learning applications through the company’s MLOps setup.
• Monitor deployed models for technical health, business outcomes, and data or concept drift.
• Translate technical work into business-friendly language for product and stakeholder communication.
• Keep documentation current and improve technical records for delivered solutions.
• Contribute to the broader Data & AI organization by strengthening technical capabilities, improving collaboration, and supporting better working practices.
• Encourage a strong data culture by sharing knowledge, supporting teammates, and taking part in team-building efforts.

Key Requirements

• Strong grounding in mathematics, statistics, machine learning, and software development, backed by a master’s degree or higher in a relevant quantitative field such as Mathematics, Statistics, Data Science, Machine Learning, Operational Research, Computer Science, Software Engineering, or Physics.
• At least 2 years of industry experience writing efficient, production-ready Python and SQL in a professional environment; more senior positions require greater experience.
• Good understanding of software engineering practices such as profiling, optimization, scalability, testing, and cost-aware development.
• Solid knowledge of statistical methods, including hypothesis testing and causal analysis.
• Strong analytical reasoning and structured problem-solving ability.
• An engineering-focused approach to building reliable applied data science solutions.
• Comfort with data visualization using Python ecosystem libraries and/or analytics and BI tools.
• Exposure to cloud platforms and their data/ML services; Google Cloud Platform experience is especially valued.
• Ability to manage the full machine learning lifecycle from development to deployment and monitoring.
• Excellent English communication skills, both verbal and written, including concise documentation and clear presentations.
• A positive, resilient mindset.
• Strong interpersonal skills with empathy, active listening, peer support, and stakeholder relationship building.
• Self-driven, motivated, and able to work independently while managing your own tasks effectively.

Nice to Have

• Background in on-demand, mobility, or financial services environments.
• Experience building machine learning features for digital products such as apps or websites.
• Exposure to pricing or economics projects and related modelling approaches, or a background in economics or econometrics.
• Experience with fraud detection, dispatching, or personalization projects.

Additional Information

The hiring process may use artificial intelligence tools to assist with resume screening, application review, or response assessment. These tools support the recruitment team but do not replace human evaluation, and final hiring decisions are made by people. If you want more information about how your data is handled, you may contact the company directly.

Join the Ride

This is an opportunity to work on important product and machine learning challenges within a fast-growing technology company and help shape the future of its data-driven solutions.