Top Tech Jobs & Startup Jobs in NYC, NY

As an Android Engineer, you'll develop native mobile applications, focusing on enhancing user experiences for financial management. You'll work with a small team on delivering key business initiatives, building scalable frameworks, and improving engineering excellence. Your role includes applying your expertise in Kotlin and Android fundamentals to deliver smooth and intuitive mobile experiences for our members.

Lead the design, development, and deployment of machine learning models and algorithms in the fintech domain. Analyze datasets to extract insights, optimize performance, and implement scalable ML pipelines using Google Cloud Platform, particularly VertexAI and Google Dataflow. Collaborate with engineering teams for model integration and contribute to best practices in machine learning.

The Backend Engineer will own the delivery of business initiatives, enhance existing architecture, and design large-scale data applications. Responsibilities include applying distributed system optimization, coding review practices, and enabling user access to decentralized finance systems.

As a Data Analyst specializing in Credit Risk, you'll develop credit risk management frameworks, optimize credit risk models, and analyze internal and external data to support product growth. You'll collaborate with stakeholders, develop data models and dashboards in Looker, and utilize a deep understanding of credit risk to enhance decision-making processes.

As a Front-End Engineer at Current, you will develop and maintain web applications, ensure high code quality, deploy production systems, and collaborate with product and design teams to enhance user experience. You will be engaged in the full lifecycle of feature development while optimizing for performance and best practices.

The Senior Product Manager will lead the full product development lifecycle for consumer-facing financial features at Current. Responsibilities include conducting customer research, defining roadmaps, collaborating with cross-functional teams, and optimizing product experiences through data analysis and experimentation.

Design and build infrastructure for data-driven features, manage the full machine learning lifecycle, enhance tooling for teams, and integrate new technologies while collaborating across departments.