Data Analytics Scientist
Role details
Job location
Tech stack
Job description
We are seeking a Data Analytics Scientist to design and deliver visualization solutions that enable learning, insight, and decision making across scientific and operational domains. In this role, you will apply analytics and data science methods to complex, high-dimensional scientific and operational data to support both development and commercial processes within the Johnson & Johnson Innovative Medicine organization. You will work with cross-functional partners to translate scientific and business questions into analytics solutions that enable diverse users to explore data and make informed decisions. Primary Responsibilities Design clear, intuitive visual analytics and dashboards for both technical and non-technical audiences, including defining the visualization strategy and roadmap. Gather requirements from scientists and translate them into clear, actionable inputs for dashboard developers, serving as the communication bridge between scientific users and the application development team. Conduct hands-on data discovery by writing queries (e.g., SQL) to explore database content and determine how to extract, join, filter, and structure data for use in visualizations. Collaborate with partners across Therapeutics Development to establish and apply advanced analytics and machine learning best practices that ensure robustness, reproducibility, and alignment with enterprise standards. Coach and support colleagues in the effective use of visualization tools as part of everyday product and process development. Stay current with emerging analytics, visualization, and Generative AI (GenAI) technologies, and support business value realization through measurable outcomes and adoption.
Requirements
Bachelor's degree or higher in Science, Engineering, or related discipline. Required Experience and Skills Experience with visualization and dashboarding tools such as Spotfire, Tableau, Power Apps/Power Automate, or PI Vision. Familiarity with enterprise or laboratory systems such as instrument control systems, sample management systems, electronic lab notebooks (eLN), and laboratory information management systems (LIMS). Exposure to pharmaceutical or life-science data, including process, analytical, or formulation data. Experience using query languages such as SQL to interact with structured data. Foundational knowledge of statistical analysis and machine learning. Demonstrated ability to communicate effectively in fluent English, both written and verbal, to diverse audiences. Organizational and project management skills, balancing multiple complex projects across global teams in agile environments (e.g., JIRA, Confluence) with effective customer management. Strong interest in digital transformation and continuous improvement, with a mindset for innovation. Ability to thrive in a fast-paced environment, combining agility, attention to detail, and structured problem-solving to deliver practical solutions. Preferred Experience and Skills Practical experience with Generative AI or LLM-based systems, including prompt design, output evaluation, and integration into analytics solutions. Experience implementing data quality checks and testing strategies to ensure reliable and trustworthy analytics and outputs. Required Skills: Preferred Skills: Analytical Reasoning, Critical Thinking, Data Savvy, Digital Fluency, Digital Strategy, Engineering, Product Design, Product Development, Product Improvements, Product Portfolio Management, Report Writing, Research and Development, Safety-Oriented, SAP Product Lifecycle Management, Statistics, Technical Credibility, Technologically Savvy
