Director, Data Science - Data Engineering

Johnson & Johnson   •  

Titusville, NJ

Industry: Healthcare


11 - 15 years

Posted 55 days ago

This job is no longer available.

The Director, Data & Analytics Engineering, part of Data Sciences team, will lead, shape and deliver data integration solutions that enable the optimal implementation of science capabilities across R&D. We support projects from discovery through late development. You will lead the team to shape & enhanced data & analytics pipelines as well as develop/deploy cut-edge technology/solutions that triangulate insights across different data domain. The role requires both a broad knowledge of existing data and analytics engineering analytics and creativity to invent and customize when necessary. You will lead a dynamic, accomplished team that supports multiple R&D therapeutic areas in the discovery and development of innovative data solutions.

In this role you will:

  • Articulate, lead and deliver the data & analytics engineering strategy for Janssen R&D Data Science community. Partner closely with Janssen R&D IT and external partners for implementation and execution
  • Work closely with R&D Data Science partners to design, build and implement data/analytical solutions to support R&D Data Science initiatives
  • Lead/Mentor a group of data engineers, analytics engineers and evolve strategies to deliver growing data & analytics engineering support
  • Lead, introduce, support, and evolve algorithms, tools and technologies that enable R&D data science initiative



  • Ph.D. with a minimum of 7 years of relevant experience (OR Master's degree with a minimum of 10 years of relevant experience) in Bioinformatics, Computational Biology, Computer Science, Information Technology, Operation Research, Statistics or a related discipline
  • People management/leadership experience
  • Familiarity with drug discovery and clinical development processes
  • Working knowledge in data analytics engineering and data integration with track record in transforming large streams, diverse of data into understandable and actionable insights
  • Understanding in clinical data model such as CDISC STDM, CDM, FHIR
  • Deep knowledge in molecular data, clinical trials data or real-world data
  • Proficient with one or more programming language such as SQL, Python, R, C++, or Java
  • Deep understanding of data and analytics lifecycle such as data wrangling, integration, and analytics workflow
  • Excellent communication, interpersonal, and written skills


  • Working knowledge of machine learning algorithms such as Random Forest, SVM, neural networks, etc. and/or Natural Language Processing techniques
  • Experience delivering on data science projects using predictive technologies, data mining and/or text mining
  • Experience working with cloud environment such as AWS, AZURE, Cloudera