Advanced Analytics Principal Engineer

Johnson & Johnson Innovative MedicineMalvern, PA
2dHybrid

About The Position

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com. As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. About Innovative Medicine: Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow. Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way. Learn more at https://www.jnj.com/innovative-medicine We are searching for the best talent for an Advanced Analytics Principal Engineer in Malvern, PA. Purpose: We are seeking an Advanced Analytics Principal Engineer to lead, design and deliver analytics solutions that enable learning, insight, and decision‑making across scientific and operational domains. In this role, you will work with complex, high‑dimensional data and apply advanced statistical analysis, data science, and AI‑assisted analytics approaches to support development and commercial processes within the Johnson & Johnson Innovative Medicine organization. You will work with cross‑functional partners to translate scientific and business questions to enable diverse users to explore data and make informed decisions.

Requirements

  • Minimum of a Bachelor's degree in Science, Engineering, Computer Science, Mathematics, or related field.
  • Minimum 6-8 years of experience applying advanced analytics
  • Experience developing analytics applications and automated reporting using languages such as Python, R, and SQL.
  • Strong foundation in statistical analysis and machine learning, with experience applying these methods to complex datasets.
  • Practical experience working with Generative AI, including prompt design, evaluation of outputs, and integration into analytics solutions.
  • Experience implementing data quality checks, testing strategies, and validation practices to ensure reliable AI outputs.
  • Strong written and verbal communication skills, with the ability to clearly explain analytical and AI‑enabled insights to diverse audiences.
  • Experience collaborating across teams and working within agile or collaborative development environments using tools such as JIRA, Confluence, Bitbucket, or similar platforms.

Nice To Haves

  • Experience with visualization and dashboarding tools such as Spotfire, Tableau, Power Apps/Automate, and PI Vision.
  • Familiarity with enterprise laboratory, or manufacturing systems, including instrument control systems, sample management systems, electronic lab notebooks (eLN), or LIMS.
  • Experience deploying or operating analytics in cloud environments such as AWS or equivalent platforms.
  • Prior exposure to pharmaceutical or life‑science data, including process, analytical, or formulation data.

Responsibilities

  • Apply advanced statistics and machine learning, including GenAI and LLM‑based approaches, to extract insight from complex scientific and operational datasets.
  • Design, develop, and maintain analytics workflows, applications, and AI‑enabled solutions that support exploratory analysis, decision support, and knowledge generation.
  • Develop clear, intuitive visual analytics and dashboards that integrate quantitative results with contextual narratives tailored to technical and non‑technical audiences.
  • Collaborate with cross‑functional partners to establish and evolve advanced analytics and AI standards to ensure adaptability, reproducibility, and alignment with enterprise standards.
  • Mentor and support colleagues in the effective use of statistical methods, analytics tools, and AI‑assisted workflows as part of everyday product and process development.
  • Stay ahead of emerging analytics, visualization, and GenAI technologies.
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