Top Tech Jobs & Startup Jobs

Owns daily New Cairo office operations, including vendor and supplier management, purchasing, maintenance coordination, workspace standards, employee support, office events, guest reception, expense reporting, and procurement budget monitoring. The role also maintains office documentation, coordinates contractors, supports employee experience initiatives, and identifies cost-saving opportunities while ensuring a welcoming and efficiently run workplace.

Leads global courier supply strategy and marketplace performance across markets. Owns supply-demand balance, courier acquisition and retention, budgets, ROI, forecasting, operating standards, product requirements, and transformation initiatives. Partners with country and cross-functional teams to improve marketplace efficiency, scale supply models, manage investments, and support future products and business growth.

Lead the end-to-end lifecycle of production-grade NLP and machine learning solutions, including research, experimentation, data pipelines, model development, deployment, monitoring, and maintenance. Translate business needs into measurable data science problems, contribute to system architecture, integrate models with backend infrastructure, address model performance issues such as concept drift, automate processes, and mentor team members.

Own analytics for marketplace matching systems, defining metrics, running A/B experiments, applying causal inference, modeling user behavior, and monitoring marketplace efficiency. Translate findings into recommendations for matching and ranking algorithms, partnering with Data Science and Engineering on production improvements. Build dashboards and analytical tools to improve visibility into marketplace health, supply-demand balance, user responses, and matching quality.

Lead the full lifecycle of production-grade NLP and machine learning models, from research and experimentation through deployment, monitoring, and maintenance. Design scalable data and ML pipelines, integrate models with backend infrastructure, address issues such as concept drift, and translate business goals into measurable outcomes. Mentor team members, improve operational efficiency, and communicate technical findings to technical and non-technical stakeholders.

Architect, develop, deploy, and maintain production-grade NLP and machine learning solutions for automating customer support operations. Responsibilities include managing the full model lifecycle, building scalable data and ML pipelines, integrating models with backend infrastructure, monitoring model performance and concept drift, defining metrics, conducting experiments, mentoring team members, and communicating findings to technical and nontechnical stakeholders.

Own and improve production forecasts for marketplace supply, demand, and financial metrics. Responsibilities include monitoring forecast quality, explaining plan-versus-actual variances, supporting budgeting and target-setting cycles, running scenario analyses, maintaining metric dependencies, investigating anomalies, validating models, and communicating assumptions to business and technical stakeholders. The role requires Python and SQL expertise, practical time-series forecasting knowledge, and ownership of production analytics workflows.

Own and improve inDrive’s production forecasting product using Python and BigQuery. Responsibilities include monitoring daily and monthly forecasts, analyzing plan-versus-actual variances, explaining business drivers, supporting budgeting and target-setting cycles, building scenario analyses, maintaining metric dependencies, investigating anomalies, validating models, and communicating assumptions and uncertainty to technical and business stakeholders.

Own inDrive’s forecasting product by monitoring daily and monthly forecasts, explaining plan-to-actual variances, supporting budgeting and target-setting cycles, running scenario analysis, and maintaining consistent supply, demand, and financial metric dependencies. Investigate anomalies across data and models, improve forecasting pragmatically, validate business impact, and maintain production Python and cloud data workflows while communicating assumptions and results to technical and business stakeholders.

Own customer lifecycle and product engagement marketing through multi-channel campaign execution, dynamic audience segmentation, automated workflows, A/B testing, deliverability management, reporting, and optimization. Present campaign insights and recommendations to stakeholders while collaborating with content, design, and analytics teams. Mentor junior CRM specialists and ensure campaigns comply with GDPR and CCPA requirements.