Jobs at CUJO AI

Build and maintain data models, ELT transformations, curated datasets, dashboards, KPI definitions, and reusable analytics assets. Partner with product, engineering, and business teams to answer questions, deliver reporting, and improve data quality. Establish analytics standards, mentor analysts, prioritize requests, troubleshoot upstream data issues, and communicate findings to technical and non-technical stakeholders.

Senior Data Analyst responsible for building data models, ELT transformations, KPI definitions, reusable datasets, dashboards, and analytics practices. The role partners with product, engineering, and business teams to answer questions, improve self-service analytics, maintain production-grade data assets, and communicate findings. Requires strong SQL, Python, dbt, Spark, data modeling, cloud warehouse, BI, testing, and stakeholder-management skills.

Build reliable data models, ELT transformations, curated datasets, dashboards, KPI definitions, and reporting for cross-functional teams. Translate business questions into analyses and actionable recommendations, maintain production-grade metrics and models, improve data quality and observability, and promote shared analytics standards through documentation, code review, mentoring, and stakeholder collaboration.

Develop machine learning algorithms, analyze large company datasets, identify anomalies and failures, build performance measurement tools, and move research into production. The role involves cross-functional collaboration, presenting research findings to stakeholders, and improving products and operations using Python, SQL, statistics, machine learning, and AWS.

Develop and maintain Python-based test automation across firmware, cloud backend, and mobile products. Design E2E and UAT coverage, investigate defects, assess release readiness, communicate quality risks, and contribute to sustainable testing strategies. The role requires networking knowledge, CI/CD integration, analytical problem-solving, cross-functional collaboration, and ownership of quality outcomes.

Build and maintain Python test automation across firmware, cloud backend, and mobile products. Design E2E and UAT coverage, assess release readiness, communicate quality risks, manage defects, and contribute to sustainable QA strategy. Collaborate with engineering and product teams in an Agile environment, investigate root causes, and improve testing practices. Networking, cybersecurity, embedded firmware, traffic capture, Linux, and CI/CD experience are valuable.

Lead Data Analyst responsible for designing big-data reports, queries, and dashboards; analyzing network data, threats, and trends; executing system change deployments; collaborating with quality and software engineers; researching improvements; and informing product design through actionable insights. The role also supports analytics process improvement, automation, reporting, stakeholder communication, and team mentoring.

Lead Data Analyst responsible for creating big-data reports, queries, and dashboards; analyzing network data and identifying trends and threats; deploying customer-facing changes; collaborating with quality and software engineers; researching solutions; improving analytics processes; influencing product decisions; and mentoring colleagues.

Lead Data Analyst responsible for designing reports, queries, and dashboards; analyzing network and big-data datasets; identifying trends and threats; deploying customer-facing changes; and supporting product decisions. The role collaborates with quality, software engineering, and leadership teams, improves analytics processes and tooling, conducts research, automates routine work, presents findings, and mentors colleagues.

Build and maintain cloud-native, serverless backend services on AWS using Node.js/TypeScript. Design RESTful APIs, own infrastructure-as-code and CI/CD, integrate with CUJO AI platforms, ensure security and reliability at scale, troubleshoot production systems, and mentor distributed engineering teams.

Design and build cloud-native, serverless backend services on AWS using Node.js/TypeScript. Implement RESTful APIs, infrastructure-as-code, and CI/CD pipelines; ensure secure, reliable systems at scale; monitor and optimize production; mentor engineers and collaborate with distributed teams.