Note: The job is a remote job and is open to candidates in USA. AppOmni is a company that prevents SaaS data breaches by delivering end-to-end SaaS security. They are looking for a Senior Data Scientist to help define and build scalable data pipelines and intelligent analytics capabilities within their platform, applying data science and large-scale data engineering to transform complex datasets into actionable insights.
Responsibilities
- 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
Skills
- 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
- Experience with Databricks
Benefits
- Stock Options: Our vision is to not just grow as a company but to grow together. By offering stock options, we are inviting you to be an integral part of our journey forward.
- 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
- A monthly wellness benefit reimbursement
Company Overview
Company H1B Sponsorship