Transform, test, deploy, and document data to deliver clean and trustworthy data for analysis to end-users and collaborate with subject matter experts, engineers, and product managers to identify the most elegant and effective data structures. By building the data lakehouse and transforming raw data into meaningful, useful data elements, help bring engineering best practices to the Data team.
As a Data Engineer Azure, you will be an expert in the design and implementation of sophisticated Azure-based data solutions in hybrid and cloud-only scenarios. You will also be a technical consultant for our customers, navigating them on their individual data project journey. The role involves developing data pipelines and learning algorithms, data migrations, and the integration of AI and machine learning to automate processes.
The Supervisor, Clinical Data Software Management, will oversee and support all clinical data management and data software engineering operations. This position also supports overseeing the implementation and design of data schemas, data modeling, data ingestion pipelines, and workflows by all product and data mart specifications to ensure high-quality data deliverables.
As part of the Engine team, you’ll play a vital role in an environment where innovation meets collaboration by creating compelling data visualizations and dashboards that tell the story behind supply metrics. Analyze supply data to identify trends and deliver regular reporting to help leadership make informed decisions.
The Data Scientist ML, part time, role will work on training ML models using data pipelines, Extraction Transformation Loading (ETL) processes, and data integration. This role will also deliver excellent customer experience by working directly with clients and customers. This role would need a commitment to 20 hours a week.
As the Staff Data Analyst on the Servicing Analytics team, you will play a pivotal role in influencing Upstart’s success. Partnering closely with our Servicing product management, operations, engineering, and ML teams, you’ll work directly with key stakeholders, helping drive understanding, insights, decision-making, and data infrastructure relating to the development, optimization, and enhancement of our recoveries and collections strategy.