Data Scientist

About Yulu

Yulu is India’s leading shared micro-mobility platform, revolutionizing urban transportation through smart, sustainable, and electric-first mobility solutions. With a rapidly growing fleet of tech-enabled electric two-wheelers and a robust battery-swapping infrastructure, Yulu makes last-mile commutes not only efficient but also planet-friendly.

Our IoT-driven platform and smart electric vehicles are helping cities reduce traffic congestion and carbon emissions while empowering millions with affordable and reliable transportation.

Backed by industry giants like Bajaj Auto and Magna International, Yulu operates at the intersection of mobility, technology, and sustainability. Our mission is to reduce congestion, cut emissions, and transform how India moves — one ride at a time.

With millions of rides completed, thousands of EVs on the road, and a rapidly expanding footprint, we’re not just building EVs — we’re building the future of urban mobility in India.

Learn more : Role Summary

Yulu is looking for a Data Scientist to work on developing and refining statistical models and Machine Learning algorithms to address real-world challenges. You will collaborate with cross-functional teams to identify analytical needs, perform exploratory data analysis, and optimize model performance. The role also involves building and maintaining data pipelines, ensuring data quality, and staying up-to-date with emerging AI / ML technologies. If you are passionate about using data to solve impactful problems and transform urban mobility, join us in our mission to reduce traffic congestion and air pollution!

Key Responsibilities

• Collect, clean, and preprocess data from diverse sources to ensure quality and accuracy.
• Develop and refine statistical models and Machine Learning (ML) algorithms to solve real-world problems.
• Collaborate with cross-functional teams (e.g., data engineering, product, and business) to identify and understand analytical needs.
• Perform exploratory data analysis (EDA) to uncover patterns, trends, and relationships in datasets.
• Evaluate model performance using appropriate metrics, and iterate to optimize accuracy and efficiency.
• Document analyses, methodologies, and best practices to maintain clear records for future reference.
• Stay up-to-date with emerging AI / ML technologies and actively explore new approaches—especially in the areas of deep learning, Generative AI, and Large Language Models (LLMs).
• Present findings and insights to both technical and non-technical stakeholders in a clear, concise manner.

Qualifications

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