Equity Research Associate, Healthcare Sector

We are seeking an Equity Research Associate (RA) to join our Global Industry Research Healthcare Team. In this role, the RA will work closely with a senior Global Industry Analyst (GIA) to support coverage across the global biopharma universe, including large-cap pharmaceutical companies and SMID-cap biotechnology companies across the U.S. and Europe. 

The ideal candidate will be a self-directed, intellectually curious team player with a strong interest in biopharma investing and the life sciences industry. This role will require the ability to analyze both scientific and financial data, evaluate drug development pipelines, leverage AI to drive research efficiencies, and synthesize complex information to inform investment decisions. 

Responsibilities for this position will include the following: 

• Maintaining industry and comparative valuation models across large-cap pharmaceutical and biotechnology companies; 

• Building and maintaining company financial models with a focus on pipeline valuation and drug-level forecasting; 

• Assessing probability of success for clinical assets and incorporating these assumptions into investment frameworks; 

• Analyzing clinical data, regulatory developments, prescription and market data, and other industry datasets to evaluate company fundamentals and competitive dynamics; 

• Performing ongoing due diligence across the global biopharma landscape, identifying emerging investment opportunities and key risks; 

• Executing complex analytical projects leveraging AI, data, and other tools under tight time constraints; 

• Staying abreast of relevant company, clinical, and industry materials, including trial readouts, regulatory updates, and scientific publications; 

• Contributing to idea generation across both long and short investment opportunities. 

Essential Skills 

• Analytical acumen and passion for markets –The ideal candidate will possess strong financial modeling skills and the ability to analyze both clinical and financial datasets, while leveraging AI and data tools to drive deeper and more efficient research. Experience modeling drug pipelines and assessing clinical probability of success is highly valued. Intellectual curiosity and a passion for understanding the scientific drivers of biopharma innovation are essential. 

• Judgment and investment focus – Successful candidates will demonstrate an ability to prioritize the most relevant information across a complex industry landscape and develop differentiated investment insights. A discerning analytical mindset and the ability to focus on the key drivers of value creation will be important. 

• Superior collaboration skills – The Research Associate will contribute meaningfully to the research efforts of the healthcare team while building strong working relationships across the firm. The ability to communicate investment views clearly, both verbally and in writing, and participate in a constructive investment dialogue is essential. 

• Growth mindset – This role requires initiative, independence, and strong ownership of research responsibilities. The successful candidate will be proactive in identifying opportunities, deepening their expertise, and contributing to the team's investment process. 

QUALIFICATIONS  

Additional qualifications and characteristics include: 

• A minimum of 3 years of relevant investment experience; 

• Prior experience in healthcare or biopharma equity research, ideally in a buy-side or sell-side research associate role; 

• Experience analyzing pharmaceutical pipelines, clinical data, and industry datasets (including prescription or market data) is preferred; 

• Financial modeling experience, including valuation frameworks for pharmaceutical and biotechnology companies; 

• Understanding of long/short investing concepts and risk management approaches is beneficial; 

• Strong analytical and problem-solving abilities; 

• High level of intellectual curiosity and willingness to engage deeply with both scientific and financial material; 

• Strong data and technology skills, including experience using tools to screen, rank, and analyze large stock universes; 

• A willingness to lead effort to integrate AI into research processes; 

• Sound judgment, strong work ethic, and the highest level of personal and professional integrity; 

• Ability to work independently and make decisions in the face of uncertainty; 

• Strong organizational skills and attention to detail; 

• Excellent written and verbal communication skills; and 

• Superior academic credentials; an undergraduate degree is required. Scientific backgrounds in biology, chemistry, bioengineering, or related fields are advantageous. Progress toward CFA/CAIA levels is additive.