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Data Scientist / Biostatistician

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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.

What they ask for

Required

  • 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.

Skills

See also

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