Play a critical role in standing up and maintaining the data pipelines and infrastructure that power AI initiatives across the company. This role is a hybrid between data engineering and MLOps —ensuring that AI engineers have clean, structured data for modeling while also building and managing the ML infrastructure for deployment, scaling, and monitoring.

Assist in maintaining and improving data visualization dashboards to track key HR metrics. Support the management and optimization of People Data processes, ensuring accuracy and efficiency. Help automate reports and validate data to maintain data integrity. Collaborate with different teams to gather requirements for data analysis. Conduct ad-hoc data analysis.

Join a global leader in government technology as a Senior Data Engineer. You’ll leverage data from application event streams, product databases, and third-party sources to help stakeholders create products and answer business questions. Revamp orchestration and execution to reduce critical data delivery times and stand up a reporting system in BigQuery from scratch.

Leverage your analytical skills to identify patterns, trends, and insights in large data sets. Use industry standard techniques to create features, clean datasets and develop pipelines to train and serve our models. Evaluate the credit risk of potential borrowers using your developed models, effectively assigning credit scores or probability of default values.

The Staff Data Engineer role involves designing, developing, and maintaining data pipelines and infrastructure to support marketing strategies, ensuring efficient data collection, storage, and analysis, requires collaboration with data scientists and stakeholders to provide high-quality data for insights and decision-making and deliver innovative solutions aligned with company's vision.

As a Senior Data Analyst (III), you will play a critical role in driving our business strategy and growth by leveraging data to calculate contribution profit, EBITDA, revenue, and credit consumption. Your work will steer short and long term decisioning, championing a data-driven culture using data to answer business questions and deliver measurable results.

As a Risk Model Analyst on the Payments Risk Analytics team, you’ll be responsible for working cross functionally with our Risk machine learning team to evaluate Risk model performance, identify gaps and recommend solutions to improve model precision and recall and create/optimize features for our risk models to consume. This role will report to the Manager of Payments Risk for NAMER and UK/EU regions.

Lead complex PIM project engagements with a team of talented developers, leads, SME’s, and architects to tackle important problems and resolve complex issues for top companies. Manage Data Management delivery, partner with clients to address challenges and future needs in a distributed environment. Proactively collaborate with co-workers and clients, with occasional on-site travel for workshops.

The Competency Lead will lead/grow some of the most complex PIM project engagements, working with a team of talented developers, leads, SME’s, and architects to resolve complex issues. This role requires a combination of technical expertise, business acumen, and client service to be successful, and serve as a partner with clients, working collaboratively to address current challenges and tackle future needs.

Work to understand what features drive a vehicle's price and predict future values. The data science team provides industry-leading, accurate, transparent analytics. Create innovative machine learning processes, deploy them on our AWS server, and develop the tools for monitoring them. Immerse yourself in automotive industry data and collaborate with technology and engineering teams.