Principal Engineer Data Science

The Principal Engineer will understand client business use cases and technical requirements, convert them into technical design, define guidelines for NFR considerations, review architecture and design for extensibility, scalability, and security, develop overall solutions for functional and non-functional requirements, resolve issues through systematic root cause analysis, and carry out POCs to validate suggested designs. The role requires expertise in predictive modeling, statistical analysis, and optimization on GCP with Generative AI fundamentals. Strong emphasis is placed on model validation, thorough testing, and proactive issue resolution to ensure reliable, high-quality outputs across the organization. The role provides exposure to enterprise-scale data ecosystems, offering opportunities for professional growth while working alongside experienced data scientists and cross-functional technology teams.

11+ years of experience in data science with focus on predictive modeling and optimization. Strong experience with Python and libraries such as Pandas, NumPy, and Scikit-learn. Knowledge of GCP, Generative AI, MLOps, and cloud architecture. Any Graduate or Any Postgraduate qualification. Prior experience mentoring junior team members and contributing to internal knowledge repositories will also be viewed favorably. Excellent verbal and written communication skills are essential, along with the ability to explain complex technical concepts clearly to both technical and non-technical stakeholders.