Senior Product Manager - Machine Learning

About Yassir

Yassir is the leading super app in the Maghreb region, set on changing the way daily services are provided. It currently operates in 45 cities across Algeria, Morocco and Tunisia, with recent expansions into France, Canada and Sub-Saharan Africa. It is backed (~$200M in funding) by VCs from Silicon Valley, Europe and other parts of the world.

We offer on-demand services such as ride-hailing and last-mile delivery. Building on this infrastructure, we are now introducing financial services to help our users pay, save and borrow digitally. We're helping usher the continent into a digital economy era, not just by serving people, but by building a marketplace that brings people what they need while infusing social values.

About the Role

Yassir's marketplace runs on decisions made millions of times a day: which driver gets which trip, what a ride should cost, when an order will arrive, which transaction looks fraudulent, who qualifies for credit. We are looking for a Product Manager who owns the machine learning systems behind those decisions and is accountable for their measurable impact on the business.

This is a product role for ML-heavy, data-intensive products. You will lead discovery from data rather than from opinion, frame business problems as problems a model can actually solve, define what success means both offline and in production, and prove impact through well-designed experiments. You will work closely with data scientists, ML engineers and data engineers, and with product and operations partners across ride-hailing, delivery and financial services.

What This Role Is (and Isn't)

This role centres on predictive and decisioning ML: ranking, matching, forecasting, pricing, risk and personalisation. Experience building LLM or agentic features is welcome, but it is not a substitute for the fundamentals below. If your ML product experience is primarily integrating third-party models or APIs into user-facing features, this role is likely not the right fit.

Responsibilities

• Data-led discovery:Identify and size ML opportunities by going into the data yourself. Diagnose where the marketplace is losing value (supply-demand imbalance, cancellations, ETA error, fraud losses, default rates) and translate it into a prioritised, quantified problem backlog.
• Problem framing:Turn business problems into well-posed ML problems: define the prediction target, the decision it informs, the unit of analysis, label availability and quality, and the cost of different error types. Know when a problem does not need ML and a rule or heuristic will do.
• Metrics and success criteria:Define the chain from model metrics (e.g. precision/recall, calibration, MAE) to product and business metrics, and own guardrail m…

Requirements

• 4+ years of product management experience, including at least 2 years owning ML-driven products that run in production and influence core business decisions (e.g. pricing, matching, ranking, forecasting, fraud, credit risk, recommendations).
• Hands-on fluency with data: you can write SQL, explore data independently and challenge an analysis without waiting for someone else to run it.
• Demonstrated experience designing, running and interpreting controlled experiments, and a solid working understanding of causal inference.
• Strong understanding of core ML concepts: supervised learning, evaluation metrics and their trade-offs, overfitting and leakage, bias, calibration, and the relationship between offline and online performance.
• A track record of shipping ML products where you can clearly articulate the problem framing, the metrics chosen, the experiment design and the measured business impact, including what went wrong.
• Experience working with distributed or remote teams across multiple markets.
• Experience in marketplaces, mobility, on-demand delivery or fintech is a strong plus.
• BSc/MSc in Engineering, Computer Science, Statistics, Data Science or a related quantitative field.