Arcus Biosciences is an exciting growth company founded on the vision of creating best-in-class cancer therapies. We are an oncology-focused biopharmaceutical company leveraging its deep cross-discipline expertise to discover highly differentiated therapies and develop a broad portfolio of novel combinations addressing significant unmet needs.
We are located in the San Francisco bay area, in the heart of the world’s largest biotechnology research hub. Arcus Biosciences offers a competitive compensation and benefits package, including aggressive participation in the growth of the company in the form of stock option grants. Arcus is an ambitious undertaking, and we fully expect our company to become a force in the discovery, development and commercialization of novel therapies for the treatment of cancer. Our employees enjoy operating in an exceptionally dynamic and cooperative environment in which the “rule book” has not yet been written.
The Sr. Clinical Data Analyst will be responsible for creating fit-for-purpose analyses, visual data displays and dashboards from diverse data types to aid in internal data consumption and decision-making. This position will report into the Head of Statistical Programming and will interact regularly with diverse stakeholders across the organization. Demonstrated abilities to prioritize work; to understand internal business, data and decision-making needs; and to communicate and collaborate with key stakeholders both within Biometrics and beyond (research, translational science, clinical science, clinical operations, safety, medical affairs and commercial) are essential.
This is a unique opportunity to join a growing Biometrics team investigating a diverse portfolio of immuno-oncology therapeutics. The ideal candidate will come with industry experience working in a regulated environment while also demonstrating know-how, flexibility and scientific curiosity to drive creative approaches to both formal and exploratory work.
Job Duties and Responsibilities
- Generate validated, reproducible, open-source software packages or tools (e.g., R/R-Shiny, Spotfire, Tableau) to replicate more formal analyses for the purposes clinical trial planning and design, internal data review, go/no-go decision-making and external publications or data releases
- Create, augment, or modify current clinical data displays to accommodate study-specific needs and requests, including means of tracking data quality, completeness and trends
- Administer and maintain user access to data displays
- Create integrated data analyses pooling data across various clinical trials or with other relevant data sources to meet business needs (e.g., real-world data analyses, tumor or indication-specific translational questions, site monitoring, safety signal detection, go/no-go decision-making), as appropriate
- Track competitor activities in company clinical and preclinical portfolio programs; provide oral and written summaries to research, clinical development and commercial leadership
- Develop therapeutic area landscape and benchmark analyses to facilitate discussions on new target selection, clinical development and commercialization strategies
- Track relevant industry news, including major announcement, press release, earnings, analyst reports etc.; effective and timely communication to internal stakeholders on high-impact events, such as competitor regulatory milestone, clinical data release etc.
- Generate strategic business and competitive insights to support business development, investor relations and corporate strategy ad hoc tasks
- Bachelor’s or Master’s degree in a data science field, e.g., statistics, mathematics, epidemiology, computer science, bioinformatics, or another field with commensurate levels of experience
- Minimum 2+ years of biotechnology or pharmaceutical experience, with (immuno-) oncology experience preferred
- Programming experience in R or Python or similar language is a must as is experience with data display and dashboard tools such as R-Shiny, Spotfire, and Tableau (or similar)
- Familiarity with reproducibility, traceability and containers (Docker) strongly preferred
- Knowledge of clinical CDISC data standards and associated requirements of working in validated environments strongly preferred
- Demonstrated ability to rapidly adapt to changing project and strategic requirements
- Interest in continuing education, particularly in the areas of business knowledge as well as technology trends for producing analyses and visualizations (particularly with an eye towards reproducibility or interactivity)
- Takes a fit-for-purpose mindset to daily work as well as long-term vision