This engineering role is within the Strategy & Operations team, building AI-first solutions to ensure every facet of Alignable is AI-powered and data-driven. You will own projects that change how the entire company runs, like customer support automation, sales agents automation, data pipelines, and internal AI tools. You'll work closely with executives and business leaders, impacting the whole company with your work on critical projects.
As a Machine Learning Data Scientist on Extend’s Risk & Fraud Machine Learning Team, you will develop and deploy cutting-edge machine learning models to detect and prevent fraud, enhance decision-making, and drive business value. You’ll work closely with product, engineering, and operations teams to build scalable, production-ready machine learning applications that support Extend’s post-purchase products.
As a Manager Data Scientist, you'll collaborate closely with business leaders to address our clients' diverse business challenges. You will lead and mentor junior data scientists, helping them achieve their goals and ensuring the team's success. This role requires strong business acumen to understand and solve complex problems, ensuring the successful implementation of data-driven solutions.
Be part of the Data Engineering team while supporting the Data Science team, where your role involves delivering clean, reliable, and automated data processes that support financial decision-making by building and optimizing data pipelines from multiple source systems into Azure Databricks, ensuring accuracy, scalability, and alignment with enterprise architecture standards.
Responsible for developing AI and ML solutions to drive improved business performance and efficiency across domains, you will lead end-to-end AI/ML projects from understanding business needs to data preparation, model development, solution deployment, and post-production monitoring. You will dissect and solve complex business problems using analytical and quantitative approaches to identify patterns and correlations in large complex data sets.
Experian's commercial division of Machine Learning and Advanced Analytics team is looking for a Data Scientist to support internal and external credit modeling projects; you'll work with analytics consultants, external clients, and other project team members to lead modeling projects from beginning to implementation.
Establish and lead the Product Science function, ensuring product decisions are grounded in rigorous experimentation, advanced analysis, and AI tools. Partner with Product, Data, Engineering, and Design, building a culture of evidence-based decision making and helping teams leverage AI in their day-to-day work.
Join the team as a Data Engineer and help improve the lives of people with diabetes through data-driven innovation. As a senior member of the Data Engineering & Analytics team, you’ll lead big data engineering and cloud-based analysis to support real-time decision-making, define scalable data strategies, and build secure, efficient pipelines. You’ll operationalize machine learning models and uncover insights across key domains.
Conduct ground breaking research in music generation (diffusion, flow matching, or autoregressive models), as well as related domains like ML-based audio processing, music information retrieval, machine learning, and signal processing. Run large-scale experiments with access to Spotify’s extensive infrastructure. Collaborate as part of a cross-functional team to craft innovative solutions to complex challenges, pushing the boundaries of what’s possible in listening experiences.
Play a pivotal role in shaping the data landscape and driving the strategic use of data across the organization, with a focus on go-to-market solutions. Be instrumental in building SSOT models in DBT & Snowflake, maintaining robust, scalable data pipelines, and enhancing our data infrastructure to support analytics and data-driven decision-making. This role is 100% remote and can be based anywhere in the United States or Canada.