Job description

AI-Driven Biotech & Pharma Equity Research We are seeking a Data Scientist / Biostatistician to join our biotech and pharmaceutical equity research team. The role will focus on building proprietary AI, machine-learning, and statistical models to predict clinical-trial outcomes and generate differentiated investment insights. Responsibilities • Build AI and statistical models to predict clinical-trial results, probability of success, regulatory outcomes, and commercial potential . • Analyze trial design, endpoints, powering, patient populations, treatment effects, safety, and subgroup data. • Use generative AI, LLMs, and natural-language processing to analyze scientific publications, regulatory documents, trial registries, company disclosures, and earnings transcripts. • Create automated tools to track pipelines, clinical catalysts, competitive programs, and emerging risks. • Convert model outputs and clinical data into clear investment conclusions. • Work with research analysts on company forecasts, pipeline valuations, and published research. • Validate models and control for bias, overfitting, data leakage, and AI hallucinations. Qualifications • PhD, MD, or master’s degree preferred in biostatistics, statistics, data science, artificial intelligence, epidemiology, bioinformatics, computational biology, medicine, or a related field. • Strong Python or R skills. • Experience building machine-learning, predictive, or generative-AI models. • Strong knowledge of clinical-trial design and statistical analysis. • Ability to explain complex scientific and quantitative findings clearly. • Interest in biotechnology, drug development, investing, and financial markets. • Equity-research experience is helpful but not required. Primary Location Full Time Salary Range of $135,000 - $165,000.

Requirements

Must-haves

AI-Driven Biotech & Pharma Equity Research
Build AI and statistical models to predict clinical-trial results, probability of success, regulatory outcomes, and commercial potential .
Analyze trial design, endpoints, powering, patient populations, treatment effects, safety, and subgroup data.
Use generative AI, LLMs, and natural-language processing to analyze scientific publications, regulatory documents, trial registries, company disclosures, and earnings transcripts.
Create automated tools to track pipelines, clinical catalysts, competitive programs, and emerging risks.
Convert model outputs and clinical data into clear investment conclusions.
Work with research analysts on company forecasts, pipeline valuations, and published research.
Validate models and control for bias, overfitting, data leakage, and AI hallucinations.
Strong Python or R skills.
Experience building machine-learning, predictive, or generative-AI models.
Strong knowledge of clinical-trial design and statistical analysis.
Ability to explain complex scientific and quantitative findings clearly.
Interest in biotechnology, drug development, investing, and financial markets.
Equity-research experience is helpful but not required.

Nice-to-haves

PhD, MD, or master’s degree preferred in biostatistics, statistics, data science, artificial intelligence, epidemiology, bioinformatics, computational biology, medicine, or a related field.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aipython

Platform: oracle-cloud
Effort: medium