Description One North is a digital experience agency that combines curiosity, scale, and agility to shape the future. As part of TEKsystems, a leading provider of business and technology services, we offer boutique solutions to solve
As passionate about our people as we are about our mission. Why Join Q2? Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, alternative finance companies, and fintechs in the
Company Description CapTech is a team of master builders, creators, and problem solvers who help clients grow efficient, successful businesses. We unite diverse skills and perspectives to transform how data, systems, and ingenuity enable each client
Wells Fargo is seeking a Principal Data Architect— a hands-on technologist who will shape modern data architecture across cloud and on-prem environments in a large-scale banking ecosystem. This role designs scalable patterns for application, analytics, workflow,
Description We are seeking a midlevel Data Engineer with hands‑on expertise in Hadoop, PySpark, Python, and real‑time streaming technologies such as Kafka. This role supports a large‑scale migration of on‑prem data and processing workloads into Google
Overview The Principal Data Engineer is a senior technical leader within AvidXchanges Data Engineering organization responsible for architecting, building, and scaling modern data platforms. In this role, you will drive the migration of legacy Azure SQL
About this role: Wells Fargo is seeking a Senior Quantitative Analytics Specialist (Senior Assistant Vice President) to support the development, implementation, and enhancement of credit risk models used for risk measurement, portfolio management, forecasting, and strategic
Essential Duties and Responsibilities: - Perform hands-on data analysis and modeling with huge data sets. - Apply data mining, NLP, and machine learning (both supervised and unsupervised) to improve relevance and personalization algorithms. - Work side-by-side
Essential Duties and Responsibilities: - Perform hands-on data analysis and modeling with huge data sets. - Apply data mining, NLP, and machine learning (both supervised and unsupervised) to improve relevance and personalization algorithms. - Work side-by-side