Biostatistics Real World Evidence Intern

US DSI Headquarters Home Office

Daiichi Sankyo US

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Join a Legacy of Innovation 125 Years and Counting!

Daiichi Sankyo Group is dedicated to the creation and supply of innovative pharmaceutical therapies to improve standards of care and address diversified, unmet medical needs of people globally by leveraging our world-class science and technology. With more than 125 years of scientific expertise and a presence in more than 20 countries, Daiichi Sankyo and its 18,000 employees around the world draw upon a rich legacy of innovation and a robust pipeline of promising new medicines to help people. In addition to a strong portfolio of medicines for cardiovascular diseases, under the Group’s 2025 Vision to become a “Global Pharma Innovator with Competitive Advantage in Oncology,” Daiichi Sankyo is primarily focused on providing novel therapies in oncology, as well as other research areas centered around rare diseases and immune disorders.   

We are currently seeking a Biostatistics Real World Evidence Intern for summer 2025. This full time position works for approximately 37.5 hours per week. 

Responsibilities:  The successful candidate will help to support the research project and is expected to help with other ongoing business projects, which entail conducting data analyses, contributing to the development of AI/ML models, and generating requested reports.
• Data Analysis:
o Apply data science techniques and software tools to analyze data sets relevant to ongoing research projects.
• Statistical Programming:
o Utilize programming languages (e.g., R, Python) to conduct data analysis and generate reports.
o Assist in the development and maintenance of data analysis tools.
o Collaborate with the team to ensure the accuracy and reproducibility of analyses.
• Report Generation:
o Prepare clear and concise reports, visualizations, and presentations summarizing analysis results.
o Collaborate with team members to communicate findings and recommendations to stakeholders.
• Team Collaboration:
o Work closely with senior biostatisticians and researchers to support ongoing projects.
o Participate in team meetings, knowledge-sharing sessions, and project discussions.
o Collaborate with cross-functional teams within the department to achieve project goals.
• Professional Development:
o Take advantage of learning opportunities, including seminars, workshops, and mentorship.
o Seek to enhance your knowledge of biostatistics, statistical methodologies, and relevant software.
 
Education/Experience: 

• Strong knowledge of Artificial Intelligence and Machine Learning (AI/ML) methodology, including data preprocessing, model training, evaluation of model performance, and visualization of results.
• Strong knowledge of statistical methodologies, in particular Survival Analysis.
• Strong analytical and problem-solving skills.
• Proficiency in statistical software and data handling techniques. Good knowledge of R and/or Python is essential.
• Excellent communication skills, both written and verbal.
• Ability to work effectively in a collaborative team environment.
• Strong attention to detail and the ability to manage and organize data.
• Enthusiasm for learning and a strong interest in AI/ML.
• Compliant with internal and external compliance practices to ensure the integrity of work and suggest innovative approaches to improve compliances and processes

 
Qualified candidates must currently be enrolled in an accredited graduate program with a concentration in data science, biostatistics, statistics or related field. Prior experience in a corporate business environment is preferred; experience in the pharmaceutical industry is a plus. 

Daiichi Sankyo, Inc. is an equal opportunity/affirmative action employer.  All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law. 

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Tags: Biostatistics Data analysis Machine Learning ML models Model training Pharma Python R Research Statistics

Perks/benefits: Career development

Region: North America
Country: United States

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