AppOmni prevents SaaS data breaches by delivering end-to-end SaaS security. Our platform gives security teams clear visibility into posture, access, third-party connections, AI-related activity, and with built-in discovery to identify unsanctioned SaaS and Shadow AI tools. Backed by continuous monitoring and real-time threat detection, AppOmni helps enterprises identify and resolve risks early, keeping their SaaS applications secure.
Recognized as a Frost Radar™ 2025 Leader and Great Place To Work®, AppOmni continues to set the standard for innovation and customer value in SaaS security. The largest and fastest-growing global enterprises across industries trust AppOmni to secure their SaaS applications.
About the Role
AppOmni is looking for a Lead Data Scientist, Risk Intelligence & AI to define and build machine-learning–driven risk scoring, prioritization, and AI-powered security workflows within our SaaS security platform.
In this role, you will apply statistical modeling, machine learning, and modern AI techniques to help transform security signals into actionable prioritization, and to develop intelligent, agent-driven product capabilities that assist customers with investigation, triage, and response. You will play a key role in shaping how AI is applied responsibly and effectively in customer-facing security workflows.
This is a hands-on individual contributor role with technical leadership responsibilities. You will work closely with Product and Engineering to design, build, and operationalize ML and AI systems that are explainable, reliable, and safe to deploy in production.
What You’ll Do
- Design and implement data-driven risk scoring and prioritization approaches across SaaS security signals.
- Lead the development of AI-powered product capabilities, including agentic and LLM-based features that support investigation, triage, and security operations workflows.
- Define and evolve explainable decision logic so customers understand why issues are prioritized or actions are recommended.
- Contribute to approaches that assess the potential scope and impact of security issues.
- Establish evaluation methods to measure model quality, effectiveness, and reliability over time.
- Incorporate product usage signals and feedback to guide continuous improvement of ML and AI systems.
- Monitor ML and AI systems in production to ensure stability, safety, and consistent behavior.
- Partner with Engineering to operationalize models and AI workflows, supporting safe deployment and iteration.
- Collaborate with Product to shape AI-driven user experiences, ensuring alignment with customer needs and trust expectations.
- Act as a technical leader and thought partner on applied ML and AI across the product area.
What We’re Looking For
- 7–10+ years of experience as a Data Scientist, Applied Scientist, or Machine Learning Engineer, with ownership of production systems.
- Strong background in statistical modeling, machine learning, and applied decision systems.
- Experience designing and shipping ML- or AI-driven product features used by customers.
- Experience applying ML or AI to decision-making systems that influence user workflows or automated outcomes.
- Comfortability working within the GCP stack, particularly big data services, such as Dataproc (pyspark), Dataflow (Apache Beam), PubSub (Apache Kafka), data lakes (storage, partitioning, searching). Also, experience with SQL, Python, and related Data Science libs (such as scikit-learn, pytorch, GCP integrations, etc).
- Experience designing or contributing to agent-like or automated workflows, including reasoning about task decomposition, tool usage, or control flow.
- Demonstrated ability to design guardrails and human-in-the-loop mechanisms for automated or AI-assisted actions.
- Experience operating ML or AI systems post-launch, including monitoring behavior, iterating based on feedback, and addressing reliability or trust issues.
- Familiarity with LLMs and agent-based approaches, with practical awareness of reliability, safety, and evaluation considerations.
- Experience in security, identity, fraud, or risk modeling domains.
- Ability to balance automation, explainability, and user trust in customer-facing systems.
- Experience partnering closely with Product and Engineering to deliver customer-facing capabilities.
- Strong written and verbal communication skills.
Culture
Our talented team is collaborative and supportive as we move quickly to research and develop new ideas, deliver new features to our customers, and iterate on ideas and innovations. We accomplish this by focusing on our five core values: Trust, Transparency, Quality, Customer Focus, and Delivery. Our team is determined to make a difference to positively impact our way of life by securing the technology that is changing the world.
AppOmni is proud to be Certified by Great Place to WorkⓇ, as we seek to build a culture where all employees feel appreciated and supported, especially with clear and honest leadership, employee recognition, and an environment that fosters innovation and collaboration.
We believe diversity fuels innovation and drives growth by bringing a wealth of different perspectives and skills. We’re committed to fostering an inclusive environment where every employee feels valued, heard, and empowered to reach their full potential. Join us in building a workplace where we can all thrive.
https://appomni.com/careers/
Compensation & Benefits
AppOmni is committed to supporting our employees' financial, professional, and personal well-being. To do this, we take a holistic view of compensation, one that values not just the immediate financial package but also the long-term growth of both our employees and our company. We're committed to pay equity and transparency and encourage all candidates to discuss their salary expectations with us early in the application process.
Our total rewards package includes the following:
- Base Salary: The annual base salary compensation range in the U.S. for this role is: $215,000 - $260,000 USD. Final offer amounts are determined by factors such as the final candidate’s skills, qualifications, and experience, as well as business considerations and peer compensation.
- 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.
- Benefits: Home office stipend, 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, and a monthly wellness benefit reimbursement. All benefits are subject to eligibility requirements and plan details.
