Sr Scientist- Data Science

Johnson & Johnson•Raritan, NJ

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. 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. 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 manager of J&J SC Data Science to: Lead Options Modeling initiatives across a portfolio of brands, supporting strategic and tactical decisions related to capacity, network design, resiliency, cost, and service. Design, build, and maintain simulation-based digital twins, incorporating demand forecasts, capacity constraints, policies, and operational variability. 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 Partner with business stakeholders to frame decision questions, define scenarios, and interpret model results into clear, actionable insights. Collaborate with business analysts, engineers, IT, and data teams to ensure that prototypes are scaled optimally with respect to adherence to business requirements, solution cost and agility to flex the solutions 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) undefined 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.

Requirements

Master’s degree in Industrial Engineering, Operations Research, Systems Engineering, Data Science, or a related field with 5+ years of relevant experience, OR PhD in a quantitative or engineering discipline with hands-on applied modeling experience.
Strong expertise in Simio and discrete-event simulation for complex operational systems.
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 various types of Operations Research models E.g. Optimization models (Linear Programming, Non-Linear Programming, Mixed Integer Programming), Simulation models (Discrete Event Models, Monte Carlo Simulations Etc.), parameter estimation models (e.g. Markov Chain Monte Carlo Etc.)
Solid understanding of supply chain concepts, such as capacity planning, manufacturing flows, network design, inventory, and service trade-offs.
Must have demonstrated competence in working with business partners to translate business requirements into digital solution features and data science models
Must have experience with deployment of open source based models into production within cloud based digital stacks.
Candidates must have demonstrated the ability to work with data engineers to leverage data pipelines for operationalizing models.
Familiarity with Azure or AWS Cloud components such as Databricks and associated big data frameworks such as Spark, PySpark etc.
Must have intermediate to high degree of expertise in tableau or similar visualization tools to created prototypes of dashboards for validation and insights delivery
Familiarity and experience with ERP systems like SAP including unstructured data sources is preferred

Nice To Haves

Experience with modeling supply chain management particularly in the healthcare industry (pharmaceuticals/medical devices) is highly desired.

Responsibilities

Lead Options Modeling initiatives across a portfolio of brands, supporting strategic and tactical decisions related to capacity, network design, resiliency, cost, and service.
Design, build, and maintain simulation-based digital twins, incorporating demand forecasts, capacity constraints, policies, and operational variability.
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
Partner with business stakeholders to frame decision questions, define scenarios, and interpret model results into clear, actionable insights.
Collaborate with business analysts, engineers, IT, and data teams to ensure that prototypes are scaled optimally with respect to adherence to business requirements, solution cost and agility to flex the solutions
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.

Benefits

Subject to the terms of their respective plans, employees are eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:
Vacation –120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year
Holiday pay, including Floating Holidays –13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave – 80 hours in a 52-week rolling period10 days
Volunteer Leave – 32 hours per calendar year
Military Spouse Time-Off – 80 hours per calendar year