Top Tech Jobs & Startup Jobs in Houston, TX

The Senior Data Modeler designs and maintains data models, supports AI-driven practices, and collaborates on data lifecycle processes. Responsibilities include translating business needs into data structures, ensuring data governance, and supporting analytics and AI use cases.

As a Senior Deployment Strategist, you will oversee the deployment of virtual assistants, manage client relationships, and drive customer service transformation for Fortune 500 clients, ensuring project success and operational efficiency.

The Senior Manager oversees funding relationships with institutional donors, manages proposal writing, ensures alignment with funder priorities, and leads donor stewardship efforts.

Lead the development of FP&A function, implement modern FP&A platforms, manage budgeting and forecasting, and partner with leaders to shape financial strategies.

The Inside Sales Executive will drive new business by connecting with partners and showcasing advertising solutions, managing a sales funnel, and retaining clients through consultative guidance and relationship management.

The Data Analyst, Product will transform product data into actionable insights, manage data pipelines, and support product development decisions using data analysis and visualization skills.

As a Backend Engineer at Coral AI, you will design and build scalable backend systems, collaborate with teams, enforce best practices, and mentor engineers.

The Operations Specialist role involves supporting operational processes in healthcare to improve medication access, requiring problem-solving skills and adaptability to new technologies.

The Inbound & Performance Marketing Manager will own paid channels, website conversion, and inbound optimization, driving pipeline through campaign management and experimentation. Responsibilities include managing Google Ads, LinkedIn Ads and overseeing conversion rate optimization and analytics.

Design and implement production-grade ML systems for ICS/OT cybersecurity, build and optimize models (including NLP/LLMs), develop data pipelines and MLOps workflows, collaborate with data teams to deploy and monitor models in cloud and on-prem containerized environments, and troubleshoot production performance and resource issues.