Lead Data Scientist

Posses a Master's degree or PhD in Engineering, Statistics, Machine Learning, Computer Science, Econometrics, or related quantitative fieldsOver 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.