Analytics Engineer II

Challenging and meaningful work that transforms the lives of patients and the careers of those who do it, with a focus on data science and machine learning.

Requirements

• Hands-on design, deployment, operations, maintenance of pipelines for data science related products and machine learning solutions
• Develop and maintain cutting-edge tools and frameworks empowering data scientists to work efficiently and effectively.
• Develop a close working relationship with data science teams to facilitate and implement best practices relating to machine learning engineering, data engineering, and MLOps.
• Collaborate with stakeholders to define project objectives, formulate data-driven hypotheses and identify KPIs for analysis
• Gather, pre-process and explore large-scale structured and unstructured data from diverse sources, including clinical trials, patient records and genetic data
• Conduct exploratory data analysis (EDA) to identify patterns and anomalies in the data and propose solutions to business problems
• Develop and implement predictive models (e.g., regression, clustering, time series forecasting) to solve complex business challenges
• Communicate complex analytical findings and insights to both technical and non-technical stakeholders through clear and compelling visualizations, reports and presentations
• Stay up-to-date with the latest methodologies and best practices in statistical analysis, machine learning, and the biopharma industry
• Mentor and provide guidance to junior data scientists and actively participate in knowledge sharing and team development

Benefits

• Competitive benefits
• Services and programs that provide employees with resources to pursue their goals
• Wide variety of benefits
• Supportive culture
• Global participation in clinical trials
• Shared values of passion, innovation, urgency, accountability, inclusion and integrity

Tagged as: Data Analysis, Forecasting