
51 - 200 employees
☁️ SaaS
🔒 Cybersecurity
🏢 Enterprise
💰 Series C on 2022-12
SaaS • Cybersecurity • Enterprise
AppOmni is a company that specializes in SaaS security solutions, focusing on helping organizations secure their software-as-a-service (SaaS) ecosystems. They offer a platform that provides deep posture inspection, threat detection, and compliance management for SaaS applications. AppOmni serves various industries, including healthcare, financial services, and life sciences, by identifying data exposure risks, detecting threats, and securing connected apps. Their solutions are designed for enterprises globally and include features such as SaaS risk assessment, posture management, and zero trust security strategies.
🔥 0 minutes ago
🇺🇸 United States – Remote
💵 $190k - $215k / year
⏰ Full Time
🟠 Senior
📊 Data Scientist
🦅 H1B Visa Sponsor
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51 - 200 employees
☁️ SaaS
🔒 Cybersecurity
🏢 Enterprise
💰 Series C on 2022-12
SaaS • Cybersecurity • Enterprise
AppOmni is a company that specializes in SaaS security solutions, focusing on helping organizations secure their software-as-a-service (SaaS) ecosystems. They offer a platform that provides deep posture inspection, threat detection, and compliance management for SaaS applications. AppOmni serves various industries, including healthcare, financial services, and life sciences, by identifying data exposure risks, detecting threats, and securing connected apps. Their solutions are designed for enterprises globally and include features such as SaaS risk assessment, posture management, and zero trust security strategies.
• Design and implement scalable batch and real-time data processing systems across large and complex datasets. • Build and optimize ETL and streaming data pipelines using modern GCP big data technologies. • Support development decisions around model choices, data architecture, data modeling, pipeline orchestration, analytics infrastructure, and production systems. • Develop statistical models and analytics capabilities that support product intelligence and operational insights. • Design and maintain production-grade data workflows using technologies such as Airflow, Dataflow, PubSub, and PySpark. • Contribute across multiple areas of the data ecosystem, including data engineering, monitoring and governance, visualization, and analytics tooling. • Establish monitoring, observability, and governance practices for data quality, pipeline reliability, and production health. • Partner closely with Engineering to operationalize scalable data infrastructure and analytics systems. • Collaborate with Product to shape intelligent, data-driven product capabilities and user experiences. • Act as a thought partner across data engineering, analytics, infrastructure, and applied modeling initiatives. • Help evolve internal tooling and frameworks that improve scalability, reliability, and operational efficiency across the platform.
• 7–10+ years of experience as a Data Scientist, Applied Scientist, Data Engineer, or Machine Learning Engineer, with ownership of production systems. • Strong experience building and operating large-scale data pipelines and distributed data processing systems. • Hands-on experience within the GCP ecosystem, particularly big data services such as Dataproc, Dataflow, PubSub, and related storage and data lake technologies. • Strong proficiency in Python, PySpark, and modern data processing frameworks. • Experience working across multiple disciplines of the data stack, including data engineering, analytics, infrastructure, monitoring/governance, APIs, and visualization. • Experience with real-time or streaming systems and orchestration frameworks such as Airflow and Apache Beam/Dataflow. • Strong foundation in statistical modeling, analytics, and applied data science techniques. • Experience designing and maintaining scalable ETL workflows and production data infrastructure. • Familiarity with monitoring, observability, governance, and reliability practices for production data systems. • Ability to thrive in highly cross-functional environments and contribute across a wide range of technical challenges. • Demonstrated versatility — a background that spans multiple types of data applications, infrastructure, and analytics work is highly valued. • Experience partnering closely with Product and Engineering to deliver customer-facing capabilities. • Strong written and verbal communication skills. • Nice-to-have: Experience with Databricks.
• Generous paid time off • Paid company holidays • Paid floating holidays • Paid parental leave • Paid sick time and paid family leave for applicable states • Health insurance - medical, dental, and vision with HSA option • LifeWorks Employee Assistance Program • Company-provided life insurance • AD&D • STD/LTD and additional supplemental life insurance options • 401(k) and Roth retirement saving accounts • Monthly wellness benefit reimbursement
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