Senior Data Scientist
Commercial
•
Iran, Islamic Republic of, Tehrān, Tehran, Zafaraniyeh
Ready to Get on Board?
Help us shape the future of ride-hailing and urban mobility. Submit your CV and let's build smarter cities together.
What You’ll Drive Forward
The mission of the Data Scientist in the Supply (Incentive) team is to leverage statistical modeling, machine learning, and data-driven approaches to optimize business decisions and improve campaign performance in a dynamic marketplace.
Model Development: Design, develop, and implement predictive models using machine learning and AI techniques to improve the accuracy, efficiency, and effectiveness of internal and external products.
Data Integration: Identify, integrate, and leverage relevant data sources to enhance modeling capabilities, analytical insights, and data-driven decision-making within the Incentive team.
Data & Business Analytics: Translate complex business requirements into analytical frameworks, develop actionable insights, design experiments, and analyze data to support strategic decisions and business growth.
Subject Matter Expertise: Act as a subject-matter expert in machine learning and predictive modeling, providing analytical guidance and sharing knowledge with the Commercial team and other stakeholders.
Model Lifecycle Management: Own the end-to-end machine learning model lifecycle, including feature engineering, model selection, optimization, validation, deployment support, and ongoing performance monitoring.
Business Mindset: Maintain a strong understanding of business objectives, KPIs, and operational challenges to ensure analytical solutions deliver measurable impact and actionable business value.
What Powers Your Drive
3+ years of experience in Data Science, Business Analytics, or related fields, with hands-on experience solving business problems through data-driven approaches.
Strong understanding of business logic, KPIs, and data-driven decision-making processes.
Strong attention to detail, commitment to deadlines, ability to manage multiple priorities, and adaptability in a fast-paced environment.
Strong collaborative mindset with the ability to work effectively with cross-functional teams and stakeholders.
Proficiency in Python and data science libraries, including Pandas, NumPy, SciPy, Statsmodels, Scikit-learn, Seaborn, and Matplotlib, for data analysis, modeling, and visualization.
Strong SQL skills with experience working with relational and non-relational databases, writing complex queries, and retrieving and manipulating large-scale datasets.
Solid expertise in machine learning, predictive modeling, and deep learning techniques.
Software & Data Engineering: Familiarity with backend development, APIs, data pipelines, and production programming practices to support the integration and deployment of machine learning models.
Nice to Have:
Market & Business Understanding: Familiarity with research methodologies, market dynamics, and competitive analysis, with the ability to connect analytical findings to business opportunities and strategic decisions.
Collaboration & Communication: Strong communication and collaboration skills, with the ability to work effectively with diverse teams and communicate complex analytical concepts to technical and non-technical audiences.