Lead Data Scientist

This is a fully remote position, open to applicants in Egypt.

📋 Description

• Develop the data science department from a single individual into a full team, encompassing its mission, recruitment, and modeling standards.

• Take ownership of fraud detection as a product, which includes transaction and payment risk scoring, handling chargebacks and refund abuse, managing account takeovers, addressing promo abuse, and identifying anomalies among agents and merchants.

• Establish fraud thresholds in collaboration with fraud and operations teams, and advocate for the balance between loss and friction.

• Manage identity management modeling, which consists of identity resolution, record linkage, deduplication, match confidence, profile completeness scoring, and creating unified customer profiles.

• Lead the next-best-action initiatives and segmentation for tailored customer communication.

• Implement and sustain models in production with the assistance of cloud and MLOps teams, including tasks related to monitoring, drift detection, retraining, rollback, and ensuring measurable business outcomes.

• Oversee demand and stock forecasting, predictive budgeting, setting category and SKU-level targets, as well as churn and lifetime value models.

• Direct experiment design across product and marketing, which includes formulating hypotheses, determining minimum detectable effects, establishing decision rules, and conducting readouts.

• Define the scope of work with data engineering and analytics teams.

• Equip stakeholders with decisions backed by validated metrics instead of relying on notebooks.

⛳️ Requirements

• Over 7 years of experience in data science.

• At least 2 years of experience in leading or mentoring scientists.

• Valued experience as the initial or second scientist in a team.

• Proven experience with models in production, managing live traffic, monitoring, and measuring quantified effects.

• In-depth knowledge of fraud or risk modeling.

• Experience in at least one area including: identity resolution and entity matching, forecasting, churn and lifetime value, personalization, uplift modeling, or causal inference.

• Proficient in SQL, particularly with large transaction and event data in a columnar warehouse.

• Strong capabilities in Python.

• Ability to write maintainable and executable code.

• Commitment to experimental and causal rigor, including the use of quasi-experimental methods when randomization is not feasible.

• Familiarity with consumer fintech or payments, including knowledge of transactions, funnels, cohorts, and fraud patterns.

• Skill in aligning product, engineering, marketing, and commercial stakeholders on a unified problem definition.

• Experience with AI-assisted work, along with the capacity to explain all delivered outputs.

🏝️ Benefits

• Opportunity for immediate, large-scale impact on a rapidly growing business.

• Competitive compensation packages at the top of the market.

• Collaborate with leading regional talents, including team members from Talabat, Careem, Etisalat, and more.