Data Scientist (Machine Learning)

Location: Lima, Peru

Company

hirify.global designs, builds, and scales AI-powered solutions by combining data, artificial intelligence, cloud, design, and development.

What you will do

• Build and evaluate machine learning approaches for company and entity matching.
• Develop embedding- and LLM-based matching, scoring, ranking, and similarity methodologies.
• Work with messy, multilingual data including names, aliases, domains, websites, firmographic attributes, and data hierarchies.
• Define benchmark datasets, baselines, metrics, test sets, and error-analysis processes.
• Design experiments, analyze model behavior and trade-offs, and compare LLM-assisted solutions with lower-cost alternatives.
• Communicate recommendations to engineering and business stakeholders and document successful and unsuccessful experiments.

Requirements

• 5+ years of professional Data Science or Machine Learning experience.
• Strong applied machine learning fundamentals and experience with supervised and unsupervised learning, classification, NLP, embeddings, semantic similarity, and LLMs.
• Excellent Python and SQL skills.
• Working knowledge of neural networks and transformer architectures.
• Hands-on experience with TensorFlow, PyTorch, PyCaret, or equivalent machine learning frameworks.
• Strong English communication skills.

Nice to have

• Entity resolution, record linkage, deduplication, ranking, or similarity-scoring experience.
• Retrieval, clustering, or candidate-generation experience.
• Experience with Spark, Snowflake, Databricks, or BigQuery.
• Experience with company, domain, website, or firmographic data.
• Experience working with multilingual datasets.

Culture & Benefits

• High-performance culture built around empowering excellence, collaborative teamwork, respect, transparency, and efficient communication.
• Opportunity to work on AI-native transformation and scalable products with cross-functional teams.
• Environment focused on learning quickly, taking ownership, and modern ways of working.