Applied AI / Applied Science
Applied AI / Applied Science is an individual-contributor Data + AI career progressing from guided delivery to enterprise expertise without requiring people management.
- Función
- Data & Analytics
- Arquetipo
- Science
- Nivel más alto
- L7 · Distinguished Applied Scientist
Para qué existe
Applies scientific methods and advanced AI/ML research to product and business problems, bridging experimentation and production impact.
Responsabilidades típicas
Deliver applied ai / applied science outcomes; apply data/AI standards; manage quality, reliability and risk; collaborate across product, engineering, security, legal and business teams; at senior levels shape enterprise standards and strategy.
Dónde se trabaja
Technology companies, data/cloud platforms, financial services, consulting, shared services, product engineering and regulated enterprises adopting Data + AI.
Cómo avanza la carrera
Associate Applied Scientist → Applied Scientist → Senior Applied Scientist → Staff Applied Scientist → Principal Applied Scientist → Senior Principal Applied Scientist → Distinguished Applied Scientist
Niveles de esta carrera
Seis etapas estándar. La séptima existe solo donde la carrera la contempla.
- L1Associate Applied Scientist
- L2Applied Scientist
- L3Senior Applied Scientist
- L4Staff Applied Scientist
- L5Principal Applied Scientist
- L6Senior Principal Applied Scientist
- L7Distinguished Applied Scientist
Nivel distinguido opcional. No todas las carreras llegan acá.
Qué se espera en L1 · Associate Applied Scientist
Apply applied ai / applied science capability at learns the discipline and executes defined work with guidance.
Las cinco dimensiones que cambian
- Autonomía
- Close guidance
- Alcance
- Learns the discipline and executes defined work with guidance.
- Complejidad
- Defined
- Influencia
- Immediate team
- Impacto en el negocio
- Task/team
- Ambigüedad
- Low
Cómo se ve un buen desempeño
Produces trustworthy applied ai / applied science outcomes, makes sound trade-offs, communicates evidence and risks, and demonstrates the autonomy and impact expected at L1.
Evidencia típica
Completed applied ai / applied science work products or production outcomes; documented decisions; measurable improvements in quality, reliability, risk, speed, cost or business outcomes; peer/stakeholder evidence of L1 scope.
Habilidades esperadas en L1
Agrupadas en humanas, profesionales y técnicas. La proficiencia meta usa la escala P1–P7, y cada fila dice qué significa ese nivel para esa habilidad.
Humanas6
| Humanas | P | De apoyo |
|---|---|---|
| Clear verbal communicationCommunication & Language | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Clear verbal communication; works with close guidance. |
| Clear written communicationCommunication & Language | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Clear written communication; works with close guidance. |
| CollaborationCollaboration & Relationships | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Collaboration; works with close guidance. |
| Critical thinkingThinking & Problem Solving | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Critical thinking; works with close guidance. |
| Cross-functional collaborationCollaboration & Relationships | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Cross-functional collaboration; works with close guidance. |
| Structured problem solvingThinking & Problem Solving | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Structured problem solving; works with close guidance. |
Profesionales6
| Profesionales | P | De apoyo |
|---|---|---|
| AI governanceData & Analytics Practice | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of AI governance; works with close guidance. |
| Data ethicsData & Analytics Practice | P1AwarenessCentral | Understands the purpose, vocabulary and basic principles of Data ethics; works with close guidance. |
| Experiment designData & Analytics Practice | P1AwarenessCentral | Understands the purpose, vocabulary and basic principles of Experiment design; works with close guidance. |
| Model risk managementData & Analytics Practice | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Model risk management; works with close guidance. |
| Responsible AI principlesData & Analytics Practice | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Responsible AI principles; works with close guidance. |
| Statistical inferenceData & Analytics Practice | P1AwarenessCentral | Understands the purpose, vocabulary and basic principles of Statistical inference; works with close guidance. |
Técnicas8
| Técnicas | P | De apoyo |
|---|---|---|
| Deep learningData Science, ML & AI | P1AwarenessCentral | Recognizes the purpose, core concepts and risks of Deep learning; performs only guided exercises. |
| LLM evaluation and benchmarkingData Science, ML & AI | P1AwarenessDe apoyo | Recognizes the purpose, core concepts and risks of LLM evaluation and benchmarking; performs only guided exercises. |
| LLM fine-tuning and PEFTData Science, ML & AI | P1AwarenessDe apoyo | Recognizes the purpose, core concepts and risks of LLM fine-tuning and PEFT; performs only guided exercises. |
| Large language modelsData Science, ML & AI | P1AwarenessCentral | Recognizes the purpose, core concepts and risks of Large language models; performs only guided exercises. |
| Machine learningData Science, ML & AI | P1AwarenessCentral | Recognizes the purpose, core concepts and risks of Machine learning; performs only guided exercises. |
| Model evaluationData Science, ML & AI | P1AwarenessDe apoyo | Recognizes the purpose, core concepts and risks of Model evaluation; performs only guided exercises. |
| Natural language processingData Science, ML & AI | P1AwarenessCentral | Recognizes the purpose, core concepts and risks of Natural language processing; performs only guided exercises. |
| Reinforcement learning for AIData Science, ML & AI | P1AwarenessDe apoyo | Recognizes the purpose, core concepts and risks of Reinforcement learning for AI; performs only guided exercises. |
Qué cambia al pasar de L1 a L2
Moving from Associate Applied Scientist to Applied Scientist means greater autonomy, complexity, scope, influence and evidence of impact—not simply more tools.
Cómo se demuestra que ya estás
Sustained evidence of operating at L2-type scope: handles representative complexity, influences expected stakeholders and produces durable measurable outcomes.
Cómo prepararse
Take on one assignment at next-level scope; seek feedback; document decisions/outcomes; mentor others where appropriate; close highest-priority skill gaps.
Carreras cercanas
Calculadas por habilidades compartidas. Es una señal para explorar, no una garantía de contratación ni de elegibilidad.
- AI Governance & Responsible AIData & Analytics13 habilidades compartidas
- AI Platform & MLOps EngineeringData & Analytics12 habilidades compartidas
- Data ScienceData & Analytics13 habilidades compartidas
- Analytics EngineeringData & Analytics10 habilidades compartidas
- Data ArchitectureData & Analytics10 habilidades compartidas
- Machine Learning EngineeringData & Analytics12 habilidades compartidas
Marco de carreras v21, activo desde 17 de agosto de 2026.