Data Scientist – Life Sciences Intelligence & Valuation Analytics

RNA Advisors; Reno (NV); On-site; USD 130,000 - 180,000; Full time

Benefits offered by this job

Relocation assistance

Comprehensive benefits

Performance bonus eligibility

Job summary

RNA Advisors is building the intelligence layer for private life sciences finance. As a Data Scientist at RNA, you will design production AI systems, analytical models, and data pipelines transforming clinical, regulatory, and financial data into valuation insights.

You may build production APIs, prototype AI workflows, and automate client deliverables, with emphasis on reproducible analytics and AI-enabled capabilities across engagements and internal products.

Qualifications

• 3–6 years of applied data science, ML, or quantitative engineering in life sciences, healthcare, or finance.
• Practical experience building and validating statistical or ML models on real-world data.
• Experience extracting, structuring, and synthesizing information from unstructured documents and text.
• Working knowledge of data pipeline design, version control, and reproducible analytical workflows.
• Clear written and verbal communication to explain technical work to non-technical stakeholders.
• Exposure to NLP, LLMs, retrieval, and evaluation of AI-generated output.
• Familiarity with vector databases, embeddings, and semantic search.

Responsibilities

• Design, build, and maintain data pipelines ingesting financial, clinical, regulatory, and commercial data.
• Develop and deploy analytical models for valuation, forecasting, benchmarking, and scenario analysis.
• Apply ML and AI techniques including NLP, LLMs, retrieval, and time-series forecasting.
• Build internal tooling and automation powering RNA Advisors' AI capabilities.
• Establish data quality, versioning, documentation, and model validation standards.
• Prototype quickly, then harden work into reliable platform components.

Skills

Applied data science

Machine learning

Unstructured data handling

Data pipelines

Communication skills

NLP/LLMs familiarity

Data visualization

Domain data familiarity

Education

Bachelor's in quantitative/scientific field

MS/PhD preferred

Tools

AWS

GCP

Azure

Containers/Serverless

Workflow orchestration

Vector databases

Job description

RNA Advisors is building the intelligence layer for private life sciences companies. We are combining valuation expertise, AI, and proprietary data to create the next generation platform for biotech and pharmaceutical investment and financial intelligence.

As a Data Scientist at RNA, you will design production AI systems, analytical models, and data pipelines that transform clinical, regulatory, commercial, and financial data into defensible valuation and commercialization insights. You will work alongside valuation professionals and senior team members, translating domain frameworks into reproducible, production-grade analytics and helping embed AI-enabled capabilities directly into both client engagements and internal product development.

This is not a narrowly scoped modeling role. You may build production APIs in the morning, prototype an AI workflow in the afternoon, and work alongside valuation professionals to automate a client deliverable the next day.

Key Responsibilities

• Design, build, and maintain data pipelines that ingest and structure financial, clinical, regulatory, and commercial data from internal and third-party sources.
• Develop and deploy analytical models supporting valuation, financial forecasting, benchmarking, scenario analysis, and AI-assisted decision support.
• Apply statistical methods, machine learning, and modern AI techniques including LLMs, retrieval, probabilistic modeling, NLP, and time-series forecasting to generate analytical signal from complex datasets.
• Build and improve the internal tooling, features, and automations that power RNA Advisors' AI-enabled intelligence capabilities.
• Establish standards for data quality, versioning, documentation, and model validation to keep outputs audit-ready and defensible.
• Prototype quickly, then harden promising work into reliable, maintainable components of the platform.
• Support engagement teams with custom analysis, data extraction, and visualization as needed.
• Evaluate and integrate new AI models, libraries, and data sources, and recommend where they add analytical or efficiency value.

Potential Projects

• Extracting structured financial information from heterogeneous documents.
• Building AI systems that assist professional valuation analysts.
• Combining financial, clinical, and regulatory signals into decision-support tools.
• Developing analytics that explain, not just predict, valuation outcomes.
• Designing evaluation frameworks for AI-assisted financial analysis.

Qualifications

• 3–6 years of applied data science, machine learning, or quantitative engineering experience, ideally with exposure to life sciences, healthcare, or financial data.
• Practical experience building and validating statistical or machine learning models on messy, real-world data.
• Experience extracting, structuring, and synthesizing information from unstructured documents and text.
• Working knowledge of data pipeline design, version control, and reproducible analytical workflows.
• Undergraduate degree in a quantitative or scientific discipline required (e.g., computer science, statistics, data science, engineering, mathematics, or a life science). Advanced degree (MS, PhD) is a plus.
• Clear written and verbal communication, with the ability to explain technical work to non-technical stakeholders.

Preferred Skills

• Experience with NLP and large language models, including retrieval, prompting, and evaluation of AI-generated output.
• Experience building production AI applications using LLMs and structured outputs.
• Experience deploying AI or data applications to AWS (preferred), GCP, or Azure using containers, serverless infrastructure, or workflow orchestration tools.
• Familiarity with document intelligence, OCR, PDF parsing, and information extraction.
• Experience evaluating LLM performance and building automated quality assurance pipelines.
• Familiarity with vector databases, embeddings, semantic search, and retrieval systems.
• Familiarity with financial or valuation concepts (DCF, comparables, probability-weighted scenarios) or a demonstrated ability to learn them quickly.
• Exposure to clinical/regulatory and financial data sources (e.g., ClinicalTrials.gov, FDA/EMA documents, Capital IQ, PitchBook, Evaluate Pharma).
• Data visualization skills (e.g., Plotly, Tableau, Power BI) and comfort building lightweight internal tools.
• Comfort operating in a fast-paced, entrepreneurial environment with evolving priorities.

Base salary: $130,000 – $180,000, commensurate with experience. Performance bonus eligibility in addition to base. Full relocation assistance and comprehensive benefits provided.

At RNA Advisors, LLC, we are building the foundational intelligence platform for private life sciences finance. Our team operates with the rigor of professional services and the velocity of a tech startup. We believe the future of biotech advisory lies in the integration of deep domain expertise with AI-enabled tools, and this role sits at the center of that thesis.

We value intellectual curiosity, collaborative problem-solving, and a commitment to translating complex data into clear, high-impact outcomes.

Location & Travel

Reno/Tahoe, NV. In-office 3–4 days per week; relocation required. Occasional travel to client sites and team meetings as needed. Must be legally eligible to work in the U.S. on a permanent basis without sponsorship.