Remote Data Jobs · US

We are seeking a Data Scientist to join our team at BMG Money. This role is crucial for transforming large, complex datasets into strategic insights that drive decision-making across various functions. The successful candidate will be responsible for independently developing, validating, and supporting the implementation of predictive models, machine learning algorithms, and advanced dashboards. This role requires strong technical mastery and the ability to work collaboratively to deliver solutions.

As a Data Scientist, you will use your coding expertise (Python, SAS), model risk management and Gen AI experience, and analytic consulting skills to lead client and internal engagements for Experian's new global product launch and early client success efforts. You will collaborate with Engineering and Data Science teams in the design and implementation of Machine Learning, Dashboarding, Ad Hoc Analysis and AI applications in a cloud-native big data (AWS) computing platform.

This role is crucial to Redzone's continued growth, focusing on leveraging performance data from our existing customer base to prove and expand our impact across customer networks. The ideal candidate is a strategic thinker with a strong analytical background, exceptional data visualization skills, and a passion for connecting operational efficiency to financial results.

Support development and maintenance of data systems used in healthcare and TPA claims processing. Assist with building and troubleshooting data pipelines while ensuring data accuracy across on-prem and cloud environments. Split time between pipeline development (50%) and operational support tickets (50%) for well-rounded experience.

Allied Global Marketing is seeking a hands-on Data Engineering Manager to architect, build, and optimize the systems that power our marketing analytics, attribution, and AI-driven insights. This role bridges marketing technology, data engineering, and analytics - ideal for a technically skilled professional who thrives on implementation, problem-solving, and precision. You’ll have full ownership in designing and deploying measurement systems.

Develop electrical system ontology for data centers which will be used to organize customer’s system data in a way where it can be used by AI & LLMs for customer facing products and services. Create and utilize tools to continuously monitor system telemetry from sensors, smart meters, and facility management systems to detect early signs of equipment degradation to help prevent service disruptions. Develop and deploy advanced anomaly detection models using machine learning and statistical methods to identify irregularities in power usage, voltage stability, cooling performance, UPS/battery behavior and more.

This role builds data pipelines that enable analytics and modeling across strategic initiatives including plant measurement and environmental controls. Day-to-day tasks include monitoring of data processing, troubleshooting and debugging data processing tasks, and development of new data flows for existing platforms. This role supports the development of data processing pipelines for Sensei Ag.

Lead and expand one of Zus's Data Acquisition (DA) teams, responsible for collecting health data from various sources and making it useful for the Zus platform. Build tools that interact with external health data networks to collect information and load it into Zus data stores. Develop and manage services used by customers to request data.

We are looking for a Senior Data Engineer with a passion for using data to discover and solve real-world problems. You will enjoy working with rich data sets, modern business intelligence technology, and the ability to see your insights drive the features for our customers. This role will contribute to the development of policies, processes, and tools to address product quality challenges in collaboration with teams.

Join the Data Science team at Blackhawk Network to help drive business value through advanced data analysis and machine learning model insights. This role focuses on key features which include building and maintaining technology systems and performing data-driven analysis on key strategic issues. This role requires direct collaboration with Data Scientists, ML Engineers, Product, and Executive teams.