Data Scientist

Location: Bengaluru

About Yulu
Yulu is India’s largest shared electric mobility-as-a-service company. Yulu’s mission is to reduce traffic congestion and air pollution by running smart, shared, and small-sized electric vehicles. Yulu is led by a mission-driven & seasoned founding team and has won several prestigious awards for its impact and innovation. Yulu is currently enabling daily commuters for short-distance movements and helping gig-workers deliver goods for the last mile with its eco-friendly rides at pocket-friendly prices and reducing carbon footprint.

Yulu is excited to welcome people with high integrity, commitment, the ability to collaborate and take ownership, high curiosity, and an appetite for taking intelligent risks. If our mission brings a spark into your eyes and if you’dlike to join a passionate team that’s committed to transforming how people commute, work and explore their cities - come, join the #Unstoppable Yulu tribe!

Stay updated on the latest news from Yulu at https://(Use the "Apply for this Job" box below). and on our website, https://.

Role Summary
Optimization & Decision Science
Formulate ambiguous business problems as mathematical optimisation and sequential decision-making problems under real-world operational constraints.
Design scalable algorithms for matching, allocation, routing, scheduling, pricing, and resource optimisation across multi-objective environments.
Develop optimisation frameworks that maximise long-term system efficiency, business value, and user experience while balancing competing objectives.
Machine Learning & Artificial Intelligence
Design, develop, and deploy production-grade machine learning systems across supervised, unsupervised, self-supervised, probabilistic, and reinforcement learning paradigms.
Develop robust feature representations and scalable learning architectures capable of operating on structured, temporal, spatial, graph, and high-dimensional datasets.
Improve model performance through principled experimentation, rigorous validation, uncertainty quantification, and continuous model adaptation.
Statistical Learning & Predictive Analytics
Develop statistically rigorous predictive models for forecasting, estimation, behavioural modelling, anomaly detection, risk assessment, recommendation, and ranking.
Apply statistical inference to quantify uncertainty, estimate causal effects, validate model assumptions, and support evidence-based decision-making.
Design models that remain calibrated, interpretable, and robust under changing data distributions and operational environments.
Time Series Intelligence
Build forecasting systems for demand, supply, pricing, utilisation, capacity planning, and operational performance across multiple temporal and spatial resolutions.
Develop probabilistic forecasting models capable of modelling trend, seasonality, uncertainty, structural breaks, and external drivers.
Design adaptive forecasting pipelines capable of continuously learning from evolving data streams.
Graph Machine Learning & Network Intelligence
Model complex relational systems using graph representations and network analytics.
Develop graph-based learning algorithms for recommendation, matching, fraud detection, routing, community discovery, knowledge graphs, and network optimisation.
Apply graph embeddings, graph neural networks, and representation learning to large-scale relational datasets.
Reinforcement Learning & Sequential Decision Systems
Develop intelligent decision-making systems where actions influence future system behaviour.
Design algorithms that optimise long-term rewards under uncertainty while balancing exploration and exploitation.
Apply reinforcement learning, contextual bandits, online learning, and sequential optimisation techniques where conventional…