Senior Applied Data Scientist

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

📋 Description

• Construct and assess ML strategies for matching companies or entities.

• Create matching techniques based on embeddings and LLMs.

• Formulate scoring and ranking systems to accurately identify genuine matches while differentiating them from duplicates, lookalikes, and unrelated entities.

• Handle complex data, which includes names, aliases, domains, websites, firmographic details, multilingual records, and hierarchical data structures.

• Establish benchmark datasets, metrics, baselines, and processes for error analysis.

• Design and implement experiments to test hypotheses.

• Evaluate LLM-assisted methods in comparison with lower-cost alternatives.

• Investigate model behavior, edge cases, and associated trade-offs.

• Factor in inference economics and scalability from the outset.

• Relay experimental results and suggestions to engineering and business stakeholders.

• Independently create experimental workflows and research methodologies.

• Thoroughly document both successful outcomes and failed experiments.

⛳️ Requirements

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

• Strong foundation in applied Machine Learning principles.

• Proficient in Python and SQL.

• Practical experience with embeddings and semantic similarity.

• Hands-on application of LLMs to tackle real-world challenges.

• Experience in both supervised and unsupervised learning methodologies.

• Significant background in classification and NLP.

• Familiarity with neural networks and transformer architectures.

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

• Experience in retraining or maintaining classification models within production environments.

• Strong skills in experimental design and model evaluation.

• Experience with defining baselines, metrics, test sets, and processes for error analysis.

• Ability to assess model quality and demonstrate quantifiable improvements.

• Solid understanding of scalability and ML inference costs.

• Proficient English communication skills.

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

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

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

• Nice-to-have: LLM/embedding solutions tailored for cost 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 working with multilingual datasets.

• Strong analytical mindset and experimental approach.

• Intellectual integrity and readiness to share negative findings.

• Demonstrated autonomy and self-direction.

• Excellent written and verbal communication capabilities.

• Ability to advocate for technical recommendations to stakeholders.

• Strong problem-solving abilities.

• Comfort in dealing with ambiguity and large-scale datasets.

• Capability to balance model quality, cost, and scalability.

🏝️ Benefits

• Availability of remote work.

• Opportunity for rapid learning and ownership.

• Collaboration with high-performing teams.

• Engagement in modern AI-native solutions and scalable products.

• A high-performance culture emphasizing Empowering Excellence, Collaborative Teamwork, Unsolicited Respect, Consistent Transparency, and Efficient Communication.