Senior Data Scientist

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:

Horsham, Pennsylvania, United States of America, Raritan, New Jersey, United States of America

Job Description:

 

SENIOR DATA SCIENTIST

 

To maintain our #1 Healthcare supply chain serving our patients, customers and parents – and remaining agile in the new digital world, J&J is looking to build capability in developing supply chain solutions that enable supporting the above initiatives.

This hybrid position may be based at any Johnson & Johnson office in New Jersey (Titusville, Horsham, or Raritan). If you are passionate about leveraging data science to address real-world challenges and foster innovation in a global environment, we encourage you to apply. 

The role requires both an in-depth knowledge of existing advanced analytics practices and approaches including Machine Learning, Mathematical Optimization, Simulation, data pipelines and advanced visualization and the ability to influence and convince others and customize and work in a multidisciplinary environment to drive business solutions. Knowledge of application of advanced analytics to manufacturing and especially pharmaceutical / healthcare / medical device manufacturing is highly desirable.

The candidate will report to director of J&J SC Data Science to:

• Gather business requirements from business partners and accurately translate those into digital & data science solution prototypes involving predictive analytics/simulation components, validate the prototypes and work closely with product development teams to scale the prototypes

• Build predictive/prescriptive model prototypes encoding complex business processes for deployment of solutions supporting business KPI improvement

• Work closely with product development teams to ensure that prototypes are scaled optimally with respect to adherence to business requirements, solution cost and agility to flex the solutions

• Work closely with vendors to deploy third party algorithmic components into our digital platforms.

• Assist digital product managers in new digital product launches i.e. ensuring that the right user tests are designed for product validation, develop metrics and product analytics to monitor and optimize products

• Assist digital product managers in sustaining and optimizing existing digital & data science products and platforms. This would involve continuous improvements to already deployed models by testing new generations of data science models, evaluating optimal ways to implement those models (e.g. open source vs vendor sourced analytic components)

• Monitor external trends on new types of modeling approaches & solution capabilities to continuously improve deployed digital solutions in targeted supply chain areas such as value chain management, planning, customer analytics, supplier risk management etc.  

Qualifications

• Masters degree in Operations Research/Econometrics/Financial Engineering/Systems Engineering or other STEM disciplines. At a minimum, 2-3 years of work experience is required.

• Must have demonstrated competence in working with business partners to translate business requirements into digital solution features and data science models

• Strong expertise in Python libraries such as numpy, scipy, pandas, scikit-learn, pyomo, simpy etc.. Proven experience demonstrating deployment of models built using python libraries in production environment

• Must have expertise in SQL, querying databases for exploratory data analysis and data profiling. Some degree of experience with NOSQL dat