Data Scientist - II (Associate)

Target Pay Rate: 50-68.12/hr **salary will be commensurate with experience

Job Description:

• Establishing data workflows and predictive tools to enable more effective identification, characterization, and development of novel medicines and vaccines is a key objective for client.
• This position sits within the Digital Sciences team in the Analytical Enabling Capabilities sub-department of Analytical Research & Development.
You will be part of a team working collaboratively across a wide range of areas impacting all aspects of the drug discovery and development pipeline.
• A diverse array of projects spanning data workflows to instrument metrology to predictive sciences ensure this Digital Sciences team helps to enable work across all drug modalities including small molecule, peptide, biologics, vaccines, and beyond.
• The core Digital Sciences team works with a networked group of digital champions across AR&D and has close connectivity to other digital/data facing teams across Research Laboratories including critical IT collaborators.

Education:
• Candidates with a degree in computer science or related field; or a degree in the chemistry disciplines with strong programming capabilities.

Experience:
• 4-6 years of experience

Must have/required skills:
• Development of dashboards, reports, and data exports
• Experience with programming in Python and deployment on Posit
• Experience with data visualization tools (Shiny, Streamlit, Dash, Spotfire, PowerBI, or Tableau)
• Excellent verbal and written communications skills
• Works independently and be able to collaborate as a team
• Strive for continuous improvement and suggest innovative solutions to scientists’ common challenges related to data visualization
• Version control using Git and GitHub
• Experience with Microsoft Power Platform (both Power BI & Power Apps) and any other similar software.
• Connecting to AWS (S3, RedShift, Glue, Athena) as a data source for data visualization

Nice to have/preferred skills:
• Experience with data pipeline tools such as Dataiku or Databricks
• Experience with relational databases and SQL
• Experience with graph databases (Neo4J or AWS Neptune)
• Experience with statistical data analysis and tools (JMP, Minitab)