Data Scientist

PhonePe is seeking a highly analytical and driven Data Scientist to join our team. This role requires a minimum of one year of professional experience and a robust foundation in scalable machine learning implementations.

The successful candidate will play a pivotal role in designing and deploying sophisticated models that drive strategic business initiatives.

Core Responsibilities:

• Model Development & Deployment: Design, develop, and deploy scalable machine learning models across diverse environments, encompassing offline batch processing, real-time online systems, and edge computing architectures.
• Advanced Analytics: Conduct rigorous analysis of complex, high-volume datasets to extract actionable insights and inform strategic business decisions.
• Cross-Functional Collaboration: Partner with engineering, product, and business stakeholders to define core challenges and formulate robust, data-driven solutions.
• Technical Communication: Synthesize and present complex quantitative findings, methodologies, and strategic recommendations to both technical and non-technical executive stakeholders.

Qualifications:

Required Qualifications:

• Education: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a closely related quantitative discipline.
• Experience: A minimum of 3 to 5 years of professional experience in a Data Scientist capacity, with a track record of deploying machine learning algorithms into production environments.
• Core Languages: Advanced proficiency in Python and SQL.
• Analytical Foundations: Deep conceptual and practical understanding of traditional machine learning algorithms, statistical modeling, linear algebra, and probability theory.
• Problem Solving: Exceptional analytical reasoning, with the ability to operate independently and navigate ambiguous data challenges.
• Communication: Outstanding written and verbal communication skills, tailored to diverse professional audiences.

Preferred Qualifications & Technical Competencies:

Candidates possessing the following supplementary skills will be given strong consideration:

• Big Data & Distributed Computing: Deep knowledge and practical experience with PySpark and other big data processing frameworks.
• Deep Learning: Proficiency leveraging neural network frameworks such as TensorFlow or PyTorch.
• Computer Vision: Working knowledge of Computer Vision concepts and algorithms.
• MLOps & Infrastructure: Familiarity with model lifecycle management tools (e.g., MLflow) and modern database architectures.
• Programming & Tools: Foundational knowledge of Java and experience with version control systems (Git).