Principal Data Scientist

5 days ago

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Amgen

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Biologics • Human therapeutics • Development of novel products

10,000+

💰 Post-IPO Debt on 2022-12

Description

• Responsible for designing, developing, and applying advanced statistical models. • Apply Generalized Linear Mixed Models (GLMM) for research problems. • Design and implement Bayesian models for predictive analytics tasks. • Perform causal inference analyses using various techniques. • Collaborate with cross-functional teams to design studies and analyze data. • Communicate complex statistical methods to non-statistical audiences clearly. • Provide mentorship and guidance to junior statisticians and data scientists.

Requirements

• Doctorate degree OR Master’s degree and 2 years of statistical modeling experience OR Bachelor’s degree and 4 years of statistical modeling experience OR Associate’s degree and 8 years of statistical modeling experience OR High school diploma / GED and 10 years of statistical modeling experience. • PhD or Master's degree in Statistics, Biostatistics, Data Science, or a related field preferred. • 5+ years of experience in applying GLMM, Bayesian modeling, and causal inference in a research or industry setting. • Proficiency in statistical programming languages such as R, Python, or SAS. • Good understanding of causal inference methods and their application to observational data and randomized control trials. • Excellent problem-solving skills and ability to translate complex statistical concepts into actionable insights. • Strong communication skills and the ability to work effectively in a team environment.

Benefits

• Comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions. • Group medical, dental and vision coverage. • Life and disability insurance. • Flexible spending accounts. • A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan. • Stock-based long-term incentives. • Award-winning time-off plans and bi-annual company-wide shutdowns. • Flexible work models, including remote work arrangements, where possible.