The role sits at the intersection of business analysis and technical data science work. The Technical Analyst is expected to understand business problems and translate them into technical requirements, and support data scientists and business stakeholders by building the infrastructure and tools needed for analytics and machine learning.
Requirements
- Python, Java, R, SQL
- Snowflake, PostgreSQL, MongoDB, Astra DB
- AWS (S3, SageMaker)
- Git, Jira, Confluence, PyCharm
- Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow, OpenCV
- Experience with large language models and GenAI frameworks
- ArcGIS, QGIS, CARTO, or Python geospatial libraries
Responsibilities
- Develop and implement data pipelines, automation, and analytical solutions
- Work with large, complex datasets (spatial, temporal, structured, and unstructured)
- Support data scientists and business stakeholders by building the infrastructure and tools needed for analytics and machine learning
- Write scripts, build APIs, create automation tools
- Maintain pipelines, ensure data quality, and enable analytics
- Develop dashboards and reports to communicate findings
- Apply GIS tools for location-based insights
Other
- Understand business problems and translate them into technical requirements
- Gather requirements, analyze processes, and document solutions
- Partner with data scientists and business users to deliver insights
- Contribute to sprint planning, backlog grooming, and testing
- Ensure best practices are captured and shared
