Senior Applied Data Scientist (ML/LLM)

Location: Warsaw, Poland; hybrid

Company

hirify.global connects talent with product careers at high-growth companies, and this role supports a global management consultancy focused on strategy, transformation, and performance improvement.

What you will do

• Develop and test ML, embedding, and LLM-based approaches for matching company records across multiple data sources.
• Handle messy entity data, including name variations, aliases, domains, websites, firmographic attributes, multilingual records, and data hierarchies.
• Build scoring, ranking, retrieval, similarity, clustering, and candidate-generation approaches to distinguish accurate matches, duplicates, similar records, and unrelated entities.
• Define evaluation methods, benchmark sets, metrics, experiments, hypotheses, and error analyses for match quality.
• Explore LLM-assisted review and validation while considering accuracy, scalability, latency, explainability, and cost.
• Partner with data and software engineering teams to productionize successful prototypes, specify expected behavior and edge cases, investigate regressions, and recommend improvements.

Requirements

• 5–8 years of relevant experience in Data Science, Applied Data Science, Applied Machine Learning, or a similar role.
• Strong applied ML fundamentals and hands-on experience building and evaluating models on real data.
• Excellent Python and SQL skills.
• Practical experience with embeddings, semantic similarity, LLMs, or related AI techniques.
• Hands-on experience training supervised and unsupervised models, including classification and NLP tasks.
• Working knowledge of neural network and transformer architectures.
• Proficiency with TensorFlow, PyTorch, and PyCaret.
• Experience retraining taxonomy classifiers or maintaining classification models in production.
• Ability to define baselines, metrics, test sets, and error analyses, and to explain model behavior, tradeoffs, and edge cases to engineering and business partners.
• Experience with entity resolution, record linkage, deduplication, or similar matching problems.
• Experience applying LLMs or embeddings to business problems where cost and scale matter.
• Exposure to large-scale data platforms such as Spark, Snowflake, Databricks, or BigQuery, plus familiarity with company, domain, website, firmographic, or other business-entity data.

Culture & Benefits

• Hybrid work arrangement in Warsaw, Poland.
• Work on complex business challenges involving large-scale data matching and applied AI.
• Close collaboration with data engineering and software engineering teams.

Hiring process

• hirify.global interview with a recruiter.
• Technical interview.
• Final interview.