Senior Applied Data Scientist - NLP, LLMs & Embeddings

Applaudo; México; On-site; MXN 600,000 - 900,000; Full time

Job summary

Applaudo is seeking an experienced Data Scientist with strong applied ML expertise to build and evaluate models on large, messy data, including embeddings, semantic similarity, NLP, and both supervised and unsupervised learning.

You will work autonomously, design experiments with clear baselines and metrics, and communicate trade-offs to engineering and business teams, while optimizing for scalability and cost.

Qualifications

• 5+ years of professional Data Science / Machine Learning experience.
• Strong applied Machine Learning fundamentals.
• Excellent Python and SQL skills.
• Hands-on experience with embeddings and semantic similarity.
• Practical experience applying LLMs to real-world problems.
• Experience with supervised and unsupervised learning.
• Strong experience with classification and NLP.
• Working knowledge of neural networks and transformer architectures.
• Hands-on experience with TensorFlow, PyTorch, PyCaret, or equivalent ML frameworks.
• Experience retraining or maintaining classification models in production.
• Strong experimental design and model evaluation skills.
• Experience defining baselines, metrics, test sets, and error-analysis processes.
• Ability to evaluate model quality and demonstrate measurable improvements.
• Strong understanding of scalability and ML inference costs.

Responsibilities

• Build and evaluate ML approaches for company/entity matching.
• Develop embedding and LLM-based matching approaches.
• Develop scoring and ranking methodologies to identify true matches and distinguish them from duplicates, lookalikes, and unrelated entities.
• Work with messy data, including names, aliases, domains, websites, firmographic attributes, multilingual records, and data hierarchies.
• Define benchmark datasets, metrics, baselines, and error-analysis processes.
• Design and execute experiments to validate hypotheses.
• Compare LLM-assisted approaches against lower-cost alternatives.
• Analyze model behavior, edge cases, and trade-offs.
• Consider inference economics and scalability from the beginning.
• Communicate experimental findings and recommendations to engineering and business stakeholders.
• Independently establish experimental pipelines and research approaches.
• Clearly document both successful and unsuccessful experiments.

Skills

DS experience

Python

SQL

Embeddings

LLMs

NLP

Transformers

TensorFlow

PyTorch

PyCaret

Experiment design

Model evaluation

Tools

TensorFlow

PyTorch

PyCaret

Job description

Applaudo is seeking an experienced Data Scientist with strong applied ML expertise to build and evaluate models on large, messy data, including embeddings, semantic similarity, NLP, and both supervised and unsupervised learning.

You will work autonomously, design experiments with clear baselines and metrics, and communicate trade-offs to engineering and business teams, while optimizing for scalability and cost.