Data Scientist

This is a fully remote position, open to applicants in Peru.

📋 Description

• Develop and assess machine learning strategies for matching companies/entities.

• Create embedding and LLM-based matching techniques.

• Formulate scoring and ranking methods to pinpoint genuine matches while differentiating them from duplicates, lookalikes, and unrelated entities.

• Manage complex data, including names, aliases, domains, websites, firmographic attributes, multilingual records, and data hierarchies.

• Establish benchmark datasets, metrics, baselines, and error-analysis procedures.

• Design and implement experiments to test hypotheses.

• Compare LLM-assisted methods with more cost-effective alternatives.

• Evaluate model performance, edge cases, and trade-offs.

• Incorporate inference economics and scalability considerations from the outset.

• Present experimental results and recommendations to engineering and business stakeholders.

• Independently create experimental pipelines and research methodologies.

• Thoroughly document both successful and failed experiments.

⛳️ Requirements

• Minimum of 5 years of professional experience in Data Science / Machine Learning.

• Solid foundation in applied Machine Learning principles.

• Proficient in Python and SQL.

• Practical experience with embeddings and semantic similarity.

• Hands-on experience applying LLMs to real-world challenges.

• Familiarity with supervised and unsupervised learning techniques.

• Substantial experience in classification and natural language processing (NLP).

• Basic knowledge of neural networks and transformer architectures.

• Practical experience with TensorFlow, PyTorch, PyCaret, or similar ML frameworks.

• Experience in retraining or maintaining classification models in a production environment.

• Strong skills in experimental design and model evaluation.

• Experience in defining baselines, metrics, test sets, and error-analysis processes.

• Ability to assess model quality and demonstrate quantifiable improvements.

• In-depth understanding of scalability and ML inference costs.

• Strong English communication abilities.

• Nice-to-have: experience in entity resolution, record linkage, or deduplication.

• Nice-to-have: familiarity with ranking and similarity scoring methods.

• Nice-to-have: knowledge of retrieval, clustering, or candidate-generation techniques.

• Nice-to-have: LLM/embedding solutions designed for cost efficiency and scalability.

• Nice-to-have: experience with Spark, Snowflake, Databricks, or BigQuery.

• Nice-to-have: background in company, domain, website, or firmographic data.

• Nice-to-have: experience handling multilingual datasets.

• Strong analytical skills and an experimental mindset.

• Commitment to intellectual honesty and a willingness to report negative findings.

• High degree of autonomy and self-direction.

• Exceptional written and verbal communication skills.

• Ability to advocate for technical recommendations with stakeholders.

• Strong problem-solving capabilities.

• Comfort in navigating ambiguity and managing large-scale datasets.

• Ability to balance model quality, cost, and scalability effectively.

🏝️ Benefits

• Option for remote work.

• Full-time employment.