Role description
Sr Data Scientist - Operations
Lead I - Data Science
The Global Deliver - Innovative Medicines team is currently seeking a skilled Sr Data Scientist- Operations Research to join our team. This role will focus on enhancing our analytics portfolio within IM (Innovative Medicines) Global Deliver through advanced modeling and simulation techniques.
The opportunity:
• Simulation & Modeling: Simulate different scenarios based on variability in supply and demand.
• Model flow of products across the distribution network (incl. different modes of transportation).
• Model the operations of the nodes in the network (incl. capacity, capability, etc).
• Model different trade-off parameters like service / cost / capacity / network / resilience
• Business and Technical Support: Support users in adopting the tools. Put processes in place to maintain and expand the models.
• Collaborate with the technical teams on development and support.
This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required.
What you need:
• Education: Master's in Data Science, Statistics, Computer Science or Supply Chain.
• Experience: Minimum of 4 years of experience in data science or analytics roles, preferably within the pharmaceutical or logistics sectors.
• Consistent track record of developing simulation and modeling in supply chain networks.
• Technical Skills: Proficiency in programming languages such as Python for data analysis and modeling.
• Experience with supply chain optimization tools like Lyric, AIMMS, etc.
• Experience with Operations Research (optimization algorithms).
• Soft Skills: Excellent communication skills with the ability to present complex data insights to non-technical stakeholders.
• Strong problem-solving skills and the ability to work independently as well as collaboratively across teams.
• Preferred Qualifications: Knowledge of pharmaceutical regulations related to distribution and transportation.
• Familiarity with machine learning algorithms and their application in logistics.
Compensation can differ depending on factors including but not limited to the specific office location, role, skill set, education, and level of experience. UST provides a reasonable range of compensation for roles that may be hired in various U.S. markets as set forth below.
Role Location: Remote-US
Compensation Range: $86,000-$129,000
Benefits
Full-time, regular employees accrue a minimum of 10 days of paid vacation per year, receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year), 10 paid holidays, and are eligible for paid bereavement leave and jury duty. They are eligible to participate in the Company's 401(k) Retirement Plan with employer matching. They and their dependents residing in the US are eligible for medical, dental, and vision insurance, as well as the following Company-paid Employee Only benefits: basic life insurance, accidental death and disability insurance, and short- and long-term disability benefits. Regular employees may purchase additional voluntary short-term disability benefits, and participate in a Health Savings Account (HSA) as well as a Flexible Spending Account (FSA) for healthcare, dependent child care, and/or commuting expenses as allowable under IRS guidelines. Benefits offerings vary in Puerto Rico.
Part-time employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year) and are eligible to participate in the Company's 401(k) Retirement Plan with employer matching.
Full-time temporary employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year) and are eligible to participate in the Company's 401(k) program with employer matching. They and their dependents residing in the US are eligible for medical, dental, and vision insurance.
Part-time temporary employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year).
All US employees who work in a state or locality with more generous paid sick leave benefits than specified here will receive the benefit of those sick leave laws.
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