Reporting to the Supervisor of Data Quality Team, the Senior Data Analyst is responsible for analyzing, reporting and enriching platform data. As part of the Common Data Platform Team, your work will enable capabilities for GHX’s data and analytics solutions utilized by hospitals and suppliers. This role is responsible for independently analyzing, debugging, documenting, and modifying data to ensure high quality data for the consumers.
As a Senior Product Data Scientist at Monzo, you will help build the bank of the future. Applying your expertise in quantitative analysis and data mining, you'll understand user interactions with products and inform product strategy. You'll guide product teams, run A/B experiments, and collaborate with finance to understand user lifetime value and feature impact.
The Data Scientist is a hybrid Data Scientist and Software Engineer, taking data from initial analysis to building pipelines to model implementation and monitoring, with full ownership of the product's back-end, responsible for harvesting insights from quantitative information collected from the mobile app ecosystem.
As a Sr. Data Scientist, you will be responsible for the entire machine learning model development process, from conception to deployment, and will partner with credit, product, and finance teams to make business decisions. You will help create and improve credit risk models, build ML based paycheck detection algorithms, and work closely with the engineering team to implement models in production.
In this role, the Junior Data Analyst will support the Lead Analyst by mining and organizing large datasets, entering and validating data, and helping visualize insights using Power BI. Great opportunity for someone early in their data career wanting to gain hands-on experience working with a high-impact, global program.
Empower is seeking a highly analytical data scientist to manage the machine learning model development process for lending products in Mexico, from conception to deployment with stakeholders. This role involves creating model pipelines, technical development, business validations, implementation, and monitoring. The ideal candidate is passionate about using data and analytics to drive business growth.