About the job
Our Journey So Far
At Snapp, we are revolutionizing urban mobility. Our innovative ride-hailing and mobility platform connects millions of riders and drivers daily, providing safe, dependable, and efficient transportation solutions. Leveraging real-time data and a robust infrastructure, we enhance urban travel, making it faster, simpler, and more sustainable.
We operate with the agility of a startup while maintaining the mindset of a global tech leader, developing scalable services that cater to diverse markets while remaining attuned to local needs.
Your Impact
As a Data Scientist on the Pricing & Growth team, your objective is to drive sustainable marketplace growth by developing and implementing AI/ML solutions in areas such as pricing, subsidy allocation, and product experimentation. You will create, refine, and launch models aimed at optimizing subsidy programs and pricing strategies, while also spearheading targeted growth initiatives. Collaborating closely with product, engineering, and operations teams, you will automate decision workflows, enhance process efficiency, and convert manual heuristics into sophisticated, production-ready AI systems with end-to-end model monitoring to achieve measurable improvements in unit economics, engagement metrics, and profitability.
What You’ll Drive Forward
In this role, you will utilize data, experimentation, and advanced AI/ML techniques to refine our pricing strategies, automate key processes, and stimulate marketplace growth. You will focus on dynamic pricing, subsidy optimization, and growth features that enhance user experience, operational efficiency, and overall profitability.
What Powers Your Drive
Machine Learning & AI
• Solid foundation in Machine Learning and Deep Learning, including:
• Neural Networks (CNN, GNN, LSTM)
• Clustering methodologies
• Time Series Forecasting
• Familiarity with Reinforcement Learning and Multi-Armed Bandits (a plus)
Programming & Frameworks
• Proficient in Python, with significant experience in:
• NumPy, Pandas, PyTorch, Scikit-learn
• Comfortable working in Linux environments.
