Senior Scientist - Machine Learning, Analytical Research and Development (Onsite

Job DescriptionDescription:Our Scientists are our Inventors. We deliver robust scientific data and interpretation that drives the commercialization of breakthrough therapeutics using innovative thinking, state-of-the-art facilities and modern equipment. Our ability to excel depends on the integrity, knowledge, imagination, skill, diversity and teamwork of people like you. To this end, we strive to create an environment of mutual respect, encouragement and teamwork. As part of our global team, you’ll have the opportunity to collaborate with talented and dedicated colleagues while developing your career.The Analytical Research and Development organization in Rahway, NJ is seeking a motivated Senior Scientist with technical expertise in predictive sciences and an ability to apply digital solutions to support our Company’s pipeline of small molecule drugs, peptides, biologics, and vaccines. Application of predictive sciences may include building models using multivariate analysis, machine learning, deep learning, generative AI, or other data science tools. The successful candidate is expected to collaboratively work with synthetic, computational, and analytical scientists, understand their problem statements, and collaboratively design and apply predictive models. There will be a strong focus on modeling large molecule stability data. The candidate must be able to work proactively and independently and influence decisions and solutions spanning a wide diversity of problem statements across our Company Research Laboratories. The role will require the candidate to network across a range of departments and effectively collaborate with stakeholders. The candidate should exemplify positive ways of working which support diversity, inclusion, and a positive culture.Primary ResponsibilitiesDesign and application of predictive models.Data curation and support in defining needs for automation of data ingestion.Influence definition of digital strategy.Application of other data science, analysis, and visualization workflows.Meet with collaborators to collect requirements.Manage projects and timelines.Presentation of updates to collaborators.Education RequirementsA Ph.D. in Chemistry, Biochemistry, Engineering, Data Science, Mathematics, Physics, Biology, Pharmaceutical Sciences, or a closely-related field.A M.S. in Chemistry, Biochemistry, Engineering, Data Science, Mathematics, Physics, Biology, Pharmaceutical Sciences, or a closely-related field with at least 2 years of relevant experience.A B.S. in Chemistry, Biochemistry, Engineering, Data Science, Mathematics, Physics, Biology, Pharmaceutical Sciences, or a closely-related field with at least 4 years of relevant experience.Required Experience and SkillsBackground and experience in machine learning, deep learning, chemometrics, multivariate analysis, generative AI, and data science.Development and application of pharmaceutically relevant predictive models.Familiar with programming in R and/or Python and Posit/RStudio/Jupyter.Experience with PyTorch or TensorFlow or Keras or TidyModels.Experience with data visualization tools (Shiny, Spotfire, Dash, PowerBI, or Tableau).Version control using Git and GitHub.Experience with data curation and analysis.Work independently and be able to collaborate as a team.Strive for continuous improvement and suggest innovative solutions to scientists’ common challenges related to data modeling.Excellent verbal and written communications skills.Preferred Experience and SkillsDemonstrated experience with modeling large molecule biological products and vaccine stability data.Knowledge of chemical matter across one or more modalities (small molecule, peptide, biologics, vaccines).Connecting to AWS (S3, RedShift, Glue, Athena, SageMaker) as a data source for data visualization.Track record of impact in the pharmaceutical industry with relevant examples directed towards pipeline objectives.Experience with data pipeline tools such as Dataiku or Databricks.Experience with relational databases, graph databases, and SQL.

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