Data Scientist

About the role

Applaudo is seeking an experienced Data Scientist to lead the design, development, and evaluation of machine‑learning solutions for large‑scale, messy data. You will work on embedding‑based matching, LLM integration, and entity resolution to improve data quality and business outcomes.

Key responsibilities

• Build and evaluate ML models for company/entity matching using embeddings and LLMs.
• Develop scoring and ranking methodologies to differentiate true matches from duplicates and unrelated entities.
• Handle noisy data sources such as names, aliases, domains, firmographic attributes, and multilingual records.
• Define benchmark datasets, metrics, baselines, and error‑analysis processes.
• Design and run experiments, compare LLM‑assisted approaches with lower‑cost alternatives, and assess inference economics.
• Communicate findings and recommendations to engineering and business stakeholders.
• Establish experimental pipelines, document outcomes, and maintain production models.

Required profile

• 5+ years of professional data‑science or machine‑learning experience.
• Strong applied ML fundamentals and a track record of working with real‑world, large‑scale data.
• Highly autonomous, intellectually honest, and able to communicate technical concepts clearly.

Required skills

• Python and SQL.
• Hands‑on experience with embeddings, semantic similarity, and LLMs.
• Proficiency in NLP, classification, supervised and unsupervised learning.
• Knowledge of neural networks, transformer architectures, TensorFlow, PyTorch, PyCaret.
• Experience with Spark, Snowflake, Databricks, or BigQuery.
• Familiarity with entity resolution, record linkage, ranking, retrieval, and clustering techniques.