Principal Data Scientist
New
A
AppOmniSaaS security
Remote - USAFull-TimePrincipal
Salary220,000 - 285,000 USD per year
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Job Details
- Experience
- 7–10+ years
- Required Skills
- PythonSQLGCPKafkaMachine LearningData scienceSpark
Requirements
- 7–10+ years of experience as a Data Scientist, Applied Scientist, or Machine Learning Engineer, with ownership of production systems.
- Experience in security, identity, fraud, or risk modeling domains.
- Probability, statistical modeling, and risk calculation expertise.
- Experience designing and shipping ML- or AI-driven product features used by customers.
- Comfortability working within the GCP stack, particularly big data services, such as Dataproc (pyspark), Dataflow (Apache Beam), PubSub (Apache Kafka), data lakes.
- Experience with SQL, Python, and related Data Science libs (scikit-learn, pytorch, GCP integrations).
- Experience designing or contributing to agent-like or automated workflows.
- 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.
- Familiarity with LLMs and agent-based approaches.
- Strong written and verbal communication skills.
Responsibilities
- Design and implement in production data-driven risk scoring and prioritization approaches across diverse large volumes of SaaS security signals.
- Lead the development and decisions on data-driven product capabilities, including data requirements, data mining, data pre-processing, data analytics, production architecture and LLM-based features.
- Define and evolve explainable decision logic so customers understand why issues are prioritized or actions are recommended.
- Establish evaluation methods to measure model quality, effectiveness, and reliability over time.
- Monitor ML and AI systems in production to ensure stability, safety, and consistent behavior.
- Partner with Engineering to operationalize models and AI workflows.
- Collaborate with Product to shape AI-driven user experiences.
- Act as a technical leader and thought partner on applied ML and AI across the product area.
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