Responsibilities
Support the identification and implementation of data analytics and AI use cases. Collect, clean, and prepare structured and unstructured datasets for analysis. Perform feature engineering and data preprocessing for machine learning models. Develop, test, and deploy AI/ML models to solve business problems. Design and maintain scalable data pipelines and ETL/ELT workflows. Analyze business data and generate actionable insights through visualization and reporting. Apply the complete data analytics lifecycle, including data discovery, modeling, validation, deployment, monitoring, and performance evaluation. Collaborate with engineering, product, and business teams to solve real-world challenges using data-driven approaches. Present analytical findings and technical concepts to both technical and non-technical stakeholders. Contribute to continuous improvements in data science methodologies and software engineering practices.
Requirements
Knowledge of Python, SQL, Snowflake, data modeling, ETL/ELT concepts, APIs, software development best practices, and version control tools such as Git. Highly adept in Snowflake Data Cloud, Python data science libraries (Pandas, NumPy, Scikit-learn), Azure cloud services, and data visualization tools such as Power BI. You are passionate about problem-solving, analytical thinking, continuous learning, collaboration, and communicating technical concepts to non-technical audiences. Valid work authorization and visa/work permit requirements applicable to the job location are required