Senior Data Scientist, Generative AI

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 https://www.jnj.com

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

New Brunswick, New Jersey, United States of America

Job Description:

We are searching for the best talent for Senior Data Scientist, Generative AI to be in New Brunswick, NJ.

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 

Purpose:

As a Data Scientist in Global Finance Data Science Team: You will be responsible for developing data science products, including the application of advanced Generative AI models, delivering practical, high-impact solutions within Global Finance. You will work alongside a global team of Data Scientists, Data Engineers, Finance Analysts and Machine Learning Engineers to advance data science and AI roadmap for J&J’s Global Finance function. You will help deliver value-added insights and analytics to our finance and business leaders, reduce manual workload through automation, and enhance user-experience.

You will help to execute the Data Science/ AI projects for Global Finance function. You will need to have a breadth of skills and knowledge to handle the challenges of translating key business needs into meaningful data science questions and investigating those questions using relevant data analytics and machine learning/ AI techniques.

You will be responsible for data science projects across their lifecycle: Prioritization of use-cases, design/ proof-of-concept (PoC), development, deployment, and adoption by end-users. The capabilities developed will include predictive financial forecasting, descriptive analytics and data visualization, decision support, cognitive/ Gen AI technologies, and data science technology platform. You will need to connect with different stakeholders to ensure the solutions meet the business and end-user needs and are widely adopted. This includes partnering with Finance Directors, CFOs and Group Finance, Commercial leaders, Process Owners, Technology, Finance Systems & Data, Reporting and Compliance teams. You will need to ensure that PoC’s are put into production with correct amount of automation and systems integration. This role will involve understanding the needs of business stakeholders and advocating the merits of Data Science/ Data-driven Analytics to provide viable solutions.

You will be responsible for:

• Develop data science solutions: Business problem understanding, data processing, algorithms to discover trends & patterns, data visualization, generation of key insights and communication to senior stakeholders. 

• Employ Generative AI techniques and approaches to upgrade Machine Learning models into hybrid models, taking advantage of LLM’s capacity to summarize, whilst seeking to reduce their capacity to hallucinate.

• Ensure that all GEN AI output adheres to rules and guidelines defined by legal, Compliance and IT.

• Write production-level and scalable code in Python or R programming languages

• Implement machine learning and statistical models for Predictive, Time series forecasting, Decision Support, Gen AI, NLP etc.

• Execute Data Science projects from an end-to-end perspective: From data acquisition, data pre-processing, modelling, visualization and full integration with end-user systems and processes.

• Develop data processing and mo