Applied Healthcare Researcher

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

📋 Description

• Act as the main technical and research liaison for discussions with healthcare clients.

• Convert model development objectives into actionable, practical healthcare data strategies.

• Assist clients in scoping opportunities and pinpointing high-value data.

• Clarify data limitations, trade-offs, and possible biases.

• Address clients' research inquiries post data delivery.

• Develop and assess methodologies, including fine-tuning, LLM-based extraction, classification, and rule-based techniques.

• Design and conduct feasibility research prior to contracts.

• Establish evidence through benchmarks, validation analyses, error characterization, and evaluations of data limitations.

• Collaborate with the Assessments team on healthcare benchmarks across various modalities.

• Assess requested variables, labels, and cohort definitions against the available healthcare data.

• Identify proxy variables or alternative dataset configurations.

• Analyze partner and source datasets for schema, field availability, quality, completeness, and transformations.

• Contribute to the company's insights on valuable healthcare data by modality and model development stage.

• Assess new data partners and datasets.

• Create reusable research, evidence, and technical materials.

• Identify repeatable workflows and collaborate with Product and Engineering to implement them.

• Expand established healthcare datasets across multiple clients.

• Engage with Solutions and FDEs from the onset of opportunities.

• Coordinate with Healthcare Data Partnerships, Product, and Engineering.

⛳️ Requirements

• Advanced degree (PhD or Master's plus 3+ years of industry experience) in machine learning, computer science, biomedical informatics, epidemiology, statistics, or a related quantitative discipline — or equivalent practical experience.

• Practical experience in building and assessing ML or LLM-based systems for extraction, classification, or prediction using real-world data.

• Familiarity with healthcare data types such as claims, EMR/EHR, clinical notes, imaging, or registries.

• Proficient in Python and SQL, with the capability to work independently with large datasets.

• Experience in designing evaluations, including assessing data quality and dataset representativeness.

• Proven ability to engage directly with technical stakeholders and convert vague objectives into solid, defensible research plans.

• Comfort in operating within a client's timeline while maintaining high research standards.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible working hours and remote work options.

• Opportunities for professional development and continuous learning.

• Supportive and inclusive company culture.