Data Scientist, Applied Intelligence

Secret Level, Inc.; Los Angeles (CA); On-site; USD 90,000 - 130,000; Full time

Job summary

Secret Level, Inc. is seeking a Data Scientist, Applied Intelligence, to help build systems for tracking workflows and supporting decision-making in creative production. This role requires 4–8 years of experience in data science, proficiency in Python and SQL, and the ability to design systems that track changes and dependencies. Collaboration with engineering and creative teams is essential, and familiarity with generative AI or media pipelines is a plus.

Qualifications

• 4–8+ years in data science, applied ML, or systems-oriented analytics.
• Strong proficiency in Python and SQL.
• Experience working with complex data systems.

Responsibilities

• Design and build intelligence systems that help track change and support outputs.
• Translate creative workflows into structured representations.
• Develop systems for tracking state, version history, and dependencies.

Skills

Data Science

Applied Machine Learning

Python

SQL

Complex Data Systems

Graph-based Reasoning

Communication Skills

Job description

Secret Level is building Liquid Engine, a production platform for AI-driven content creation. We’re developing systems that help creative workflows stay structured, consistent, and observable as they scale across tools, people, and outputs.

We’re looking for a Data Scientist, Applied Intelligence to join our Intelligence group within the broader Product and Engineering organization.

This is not a traditional analytics role. You will help design the logic, data structures, and evaluation systems that allow intelligence to operate inside a creative production environment. That includes representing workflows in structured ways, reasoning about change and dependencies, tracking provenance and version history, and building systems that support explainable, human-guided decision‑making.

You’ll work closely with engineering, product, and creative stakeholders to turn ambiguous workflow problems into reliable, measurable, and useful systems.

What You’ll Do

• Contribute to the design and build intelligence systems that help Liquid Engine understand workflow context, track change over time, and support consistent outputs
• Translate creative and production workflows into structured representations such as entities, relationships, rules, and graphs
• Help develop systems for tracking state, version history, provenance, and dependencies across workflows
• Build rule‑based and heuristic systems that identify conflicts, evaluate consistency, and surface issues before they create downstream problems
• Support change impact analysis by helping the system reason about dependencies, cascades, and workflow consequences
• Develop evaluation frameworks that measure system usefulness, output quality, and reduction of manual rework
• Partner with engineering on event pipelines, data models, and system architecture that support intelligent system behavior
• Contribute to explainable recommendation and decision‑support systems grounded in workflow context
• Help define telemetry, measurement, and governance approaches for intelligence features across the platform

What We’re Looking For

Core Skills

• 4–8+ years in data science, applied ML, or systems‑oriented analytics
• Strong Python and SQL proficiency
• Experience working with complex data systems
• Familiarity with graph‑based or relational reasoning
• Understanding of deterministic vs probabilistic systems
• Ability to translate ambiguous domains into structured approaches
• Strong communication skills across technical and non‑technical teams

Nice to Have

• Experience with generative AI systems or media pipelines
• Exposure to knowledge graphs or dependency systems
• Experience with experimentation or telemetry systems
• Familiarity with governance, audit, or compliance systems
• Experience building internal tools or operator‑facing systems

How You Work

• You think in systems, not just models
• You value clarity, explainability, and correctness
• You are comfortable operating in ambiguity
• You avoid premature abstraction or unnecessary complexity
• You collaborate closely with engineers, product, and creative teams
• You know when restraint is the right solution