• Posses a Master's degree or PhD in Engineering, Statistics, Machine Learning, Computer Science, Econometrics, or related quantitative fields
• Over 5 years of professional experience showcasing proven expertise in the development, implementation, and validation of Data Science Models, Data Engineering, and MLOps.
• Specialized skills include the development and implementation of Machine Learning algorithms such as SVM, neural networks, random forest, and XGboost, as well as expertise in hyperparameter tuning.
• Proficiency is demonstrated in scripting for data analysis using Python API, PySpark/Spark API, and familiarity with NoSQL, MYSQL, or PostgresSQL databases.
• Experience extends to building MIS infrastructure, dashboards, KPIs, and monitoring/interpreting report data to derive insights on ML model performance, business trends, and emerging risks.
• Demonstrating adeptness in model deployment and management using Docker and directory structures, the candidate possesses a robust understanding of Software Development Life Cycle (SDLC) methodologies.
• Proficient in cloud environments, particularly AWS and Snowflake.

The individual has experience operating in continuous integration, continuous delivery (CI/CD) environments and collaborates effectively with Data Engineers and Software Architects to design Data Architecture.
Additionally, the candidate has a track record of managing requirements and tasks using tools like Jira.