Develop and maintain backend and data processing systems using Python to handle large-scale geospatial imagery. Collaborate with the team to build reliable data pipelines and optimize system performance for geospatial analysis.
The Business Analyst will translate business needs into clear functional and technical requirements for web-based applications and integrated systems. They will collaborate with stakeholders, developers, and QA teams to ensure alignment throughout the development lifecycle.
Design and develop scalable backend applications and RESTful APIs using Python and AWS. Collaborate on frontend development with React and participate in the full software development life cycle for an AI-powered SaaS platform.
The Data Solutions Architect will define and govern enterprise-wide data architecture to ensure alignment with business strategy and regulatory requirements. They will lead the design of AI and machine learning platforms while driving the adoption of modern data paradigms like Data Mesh.
The Data Engineer will design and maintain scalable ETL/ELT pipelines and data platforms to support analytics and AI initiatives. They will collaborate with cross-functional teams to ensure data quality, security, and performance within financial services environments.
Design and deploy advanced machine learning models to address critical financial use cases such as credit risk, fraud detection, and customer analytics. Collaborate with cross-functional teams to build scalable data pipelines and present actionable insights to senior stakeholders.
