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
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