Associate Principal Engineer, Data Science

This is a fully remote position, open to applicants in India.

📋 Description

• Grasping the client's business use cases and technical specifications, and translating them into a technical design that effectively fulfills the requirements.

• Aligning decisions with requirements and conveying the same to developers.

• Evaluating various solutions and being able to select the optimal choice that aligns with the client’s needs.

• Establishing guidelines and benchmarks for non-functional requirements (NFR) during project execution.

• Composing and reviewing design documents that outline the overall architecture, framework, and high-level design of the application for developers.

• Assessing architecture and design across various dimensions such as extensibility, scalability, security, design patterns, user experience, and NFRs, ensuring adherence to relevant best practices.

• Crafting and designing the comprehensive solution for specified functional and non-functional requirements, defining technologies, patterns, and frameworks to realize it.

• Comprehending and relating technology integration scenarios and applying these insights in projects.

• Addressing issues raised during code reviews through thorough systematic analysis of root causes, and justifying the decisions made.

• Conducting Proofs of Concept (POCs) to ensure that proposed designs and technologies meet the requirements.

⛳️ Requirements

• A total of 9+ years of experience.

• Practical experience in data science with an emphasis on predictive modeling (e.g., Statistical Analysis, ANOVA, Time Series Analysis, Regression Analysis) and optimization.

• Proficient experience with Data Science on Google Cloud Platform (GCP) and a solid understanding of Generative AI fundamentals.

• Strong proficiency in Python (and/or R) and relevant libraries such as Pandas, NumPy, and Scikit-learn.

• In-depth knowledge of Cloud Architecture and the deployment of data solutions within cloud environments (e.g., AWS, Azure, GCP).

• Demonstrated expertise in machine learning, mathematical optimization (e.g., LP, IP, genetic algorithms, RL), and Natural Language Processing (NLP) techniques.

• Familiarity with Generative AI principles and practical experience with RAG, Lang Chain, Llama Index, and prompt engineering.

• Strong grasp of MLOps principles and tools for Continuous Integration/Continuous Deployment (CI/CD), monitoring, and model lifecycle management.

• Exceptional communication skills and the ability to collaborate effectively with cross-functional teams.

🏝️ Benefits

• Employees have the option to work remotely.