Life Sciences AI Intelligence Extern / Intern

Scientific Strategy, Key Innovation Leaders & Emerging OpportunitiesHarrison Hayes | New York / Hybrid / Remote

Harrison Hayes is seeking an unusually curious AI Life Sciences Intelligence Extern/Intern to help us identify difficult scientific and strategic problems across biotechnology, pharmaceuticals and medical technology.

This is not a conventional business development internship.

Your job is to find the questions companies don't know how to answer.

A Phase II trial fails, but a subgroup responds. A promising molecule demonstrates biological activity but insufficient differentiation. A company has six potential indications and capital for two. A regulatory agency questions whether an observed benefit can actually be attributed to the therapy. A clinically interesting asset is abandoned because it no longer competes for corporate capital.

These are the situations we want you to find.What You'll DoUsing ChatGPT, Claude, Perplexity, scientific databases and primary-source research, you will:

• Identify emerging scientific, clinical and strategic problems across life sciences
• Analyze failed or ambiguous clinical trials, pipeline changes, regulatory decisions and portfolio restructurings
• Find situations where the obvious interpretation may be incomplete
• Determine the unanswered question behind the business problem
• Identify the scientists, clinicians, regulatory experts, payers and other specialists required to answer it
• Develop concise opportunity briefs for Harrison Hayes senior leadership
• Help identify potential advisory, licensing, M&A, financing and investment opportunities arising from those insights

Why Harrison Hayes

Large consulting organizations are designed to solve broad strategic and organizational problems. Harrison Hayes is interested in something narrower and more specialized:

What happens when the problem is too scientifically specific for a generalized answer?

Through our Key Innovation Leader Networks, we assemble purpose-built groups of leading clinicians, scientists, translational researchers, regulatory specialists, payers, reimbursement experts, medical economists and former pharmaceutical executives around a single decision.

The objective is not to validate management's strategy.

It is to challenge it.

Who We're Looking For

You might be studying biotechnology, medicine, pharmacology, biomedical engineering, finance, business or data science.

More important is how you think.

You should be comfortable moving from a scientific paper to an SEC filing, from a clinical endpoint to an earnings call, and from an apparently failed drug to the question:

“Did the molecule fail, or did the experiment fail to answer the right question?”

We want someone who uses AI aggressively but skeptically. AI is your research engine.

Judgment is the job.

To Apply

Send us your résumé and a brief note explaining how you use AI for serious research.

Better yet, find us a problem.Identify one life-sciences company facing a difficult scientific or clinical decision. Tell us what happened, why the obvious interpretation may be incomplete, what management should actually be asking, and which Key Innovation Leaders you would assemble to answer it.

We are not looking for the person who finds the most information. We are looking for the person who finds the question everyone else missed.

Summary

Join our innovative team as a Life Sciences AI Intelligence Extern / Intern, where you will immerse yourself in cutting-edge artificial intelligence and machine learning projects tailored to the life sciences sector. This paid internship offers a unique opportunity to develop your skills in data analytics, statistical modeling, and AI implementation while contributing to impactful research and development initiatives. You will collaborate with experienced data scientists, bioinformaticians, and engineers to explore big data systems, natural language processing, and predictive modeling analysis that drive breakthroughs in healthcare and biological research.

Duties

• Assist in designing and implementing AI models using frameworks such as TensorFlow and machine learning cloud services to analyze complex biological datasets.
• Support the development of scalable big data systems utilizing Hadoop, Spark, and ETL processes for efficient data ingestion and processing.
• Contribute to statistical analysis for research projects employing tools like R, SAS, and statistical analysis software to derive meaningful insights.
• Collaborate on model training, evaluation, and deployment of AI models focused on predictive modeling analysis and generative AI applications.
• Help optimize database design and SQL database management to facilitate seamless data mining and data analytics workflows.
• Participate in natural language processing tasks using machine learning frameworks to analyze unstructured biomedical text data.
• Engage in cross-disciplinary teamwork to support AI implementation efforts across various life sciences research initiatives.

Experience

• Currently pursuing or recently completed a degree in Computer Science, Data Science, Bioinformatics, Statistics, or related fields.
• Familiarity with programming languages such as Python, Java, C, or Bash (Unix shell) for data manipulation and model development.
• Hands-on experience with machine learning frameworks like TensorFlow or similar tools is highly desirable.
• Knowledge of cloud services such as AWS or other machine learning cloud platforms is a plus.
• Understanding of big data technologies including Hadoop, Spark, Talend, and Looker for data processing and analytics.
• Exposure to statistical analysis tools like R or SAS for research purposes is preferred.
• Strong analytical skills with an interest in applying AI solutions within the life sciences domain are essential.

Embark on this exciting journey where your passion for AI meets the transformative world of life sciences! This paid externship is designed to empower your growth while making meaningful contributions to scientific advancements that improve health outcomes worldwide.

Work Location: Remote