Design, develop, and maintain scalable, secure, and high-performance data platforms. Build and manage data pipelines (ETL/ELT) using tools such as Apache Airflow, DBT, SQLMesh or similar. Architect and optimize lakehouse solutions (e.g., Iceberg).
Contribute to the success of our ML Underwriting team leveraging cutting-edge machine learning to assess creditworthiness throughout the life cycle of loan applications. Develop high-quality, production-ready models that play a central role in our decision-making processes. Your contributions will be instrumental in shaping our financial landscape.
The Data Infrastructure team is looking for a world-class engineer. This role drives stability, scalability and efficiency for the Houzz data ecosystem and builds critical systems that provide insights to drive growth. The candidate will architect and implement across our suite of tools that includes data pipelines, event streaming, and data warehouse/data lake.
As a Senior Software Engineer, you will define and execute the technical vision for Discord's data platform, enabling scalable, reliable, and performant data systems. You will design, implement, and optimize data infrastructure to process and analyze petabytes of data across millions of users. You will partner with data scientists, data engineers, product managers, and leadership to align technical solutions with business goals.
We are seeking an experienced Data Engineer with deep expertise in data transformation at scale, particularly in integrating and processing data from third-party public APIs. This role is critical to enhancing and maintaining data pipelines that feed into Natural Language Processing (NLP) models.
As a Data Scientist at the Experian Innovation Lab, you will help develop analytical solutions, contributing to product prototypes, and helping evaluate data assets. You will bring experience in predictive modeling, machine learning, and deep learning to this position. Refine data manipulation and retrieval through the design of efficient data structures and storage solutions.
Use Affirm’s proprietary and other third party data to develop machine learning models that predict the likelihood of default and make an approval or decline decision to achieve business objectives. Partner with platform and product engineering teams to build model training, decisioning, and monitoring systems. Research ground breaking solutions and develop prototypes that drive the future of credit decisioning at Affirm.
Your primary responsibilities will include building tools and products that enhance data science productivity, enable self-serve analytics, and ensure data reliability and quality. This role deals specifically with blockchain data. Design data models, build tooling and pipelines for blockchain data, and build mechanisms of data quality measurement and enforcement to ensure reliability and completeness of data.
You’ll play a key role in helping customers stay ahead of evolving fraud threats by designing and deploying data-driven solutions with real-world impact. You’ll work directly with clients to understand their unique fraud challenges, rapidly prototype proof-of-concept models, and build scalable, production-ready solutions using machine learning and graph analytics. This is a hands-on, high-impact role ideal for someone who thrives at the intersection of data science, client-facing problem solving, and real-time risk.
Design, build, and maintain scalable data processing systems and analytics platforms. Lead our efforts to create robust, in-house data infrastructure solutions to support our growing data needs and business intelligence requirements. Design and implement efficient data storage and processing solutions for large-scale datasets; architect a new data processing framework to replace existing third-party solutions.