Data Scientist – Optimization (Remote)

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Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow—people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level.

Job Description: JOB SUMMARY This position builds and implements models to yield predictive and prescriptive insights from large volumes of structured and unstructured data. This position works with a data science and machine learning team responsible for production-grade solutions focused on optimizing processes within airline and transportation systems, with a strong focus on real-time decision-making. This position leverages emerging tools and technologies for data analytics, visualization, optimization and machine learning available in on-prem and cloud environments. This position works with architects, data engineers, ML engineers and data scientists to prioritize opportunities and identify the most optimal tools and techniques to solve each unique problem.

RESPONSIBILITIES

Process/problem discovery and Exploratory Data Analysis Clearly communicates results, insights and recommendations through presentations and reports to a diverse group of stakeholders, iterates as needed based on business objectives Researches and identifies all possible ways to solve each problem, articulating pros and cons and working with business and technical teams to choose a path forward Problem formulation for OR-relevant problems, to include linear, integer and mixed integer programming Builds, validates, tests models toward those criteria using a combination of OR and ML tools Creates repeatable solutions through written project documentation, process flowcharts, and commented clean code Collaborates with deployment team for production handoff Tracks models in MLOPs lifecycle for performance and establishes criteria for model retraining Leverages emerging tools and technologies together with the use of open-source or vendor products in the creation and delivery of insights that support predictive and prescriptive solutions

QUALIFICATIONS Requirements:

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Bachelor’s degree in a quantitative field of mathematics, computer science, economics, engineering, statistics, operations research, or international equivalent 3+ years experience building data science and machine learning solutions, focusing on optimization, outside of an academic environment Strong analytical skills and attention to detail Able to translate business problems to analytics solution approach Expertise with statistical techniques, machine learning or operations research and their application in business applications Expertise Python Experience in launching batch and real-time ML/OR projects in production Experience implementing open-source technologies and cloud services; with or without the use of enterprise data science platforms. Solid oral and written communication skills, especially around analytical concepts and methods. Ability to communicate data through a story framework to convey data-driven results to technical and non-technical audience.

Preferences:

Master’s degree or PhD in a quantitative field of mathematics, computer science, economics, engineering, statistics, operations research, or international equivalent Experience building logistics simulations with SimPy or vendor-based tools such as AnyLogic

FOR INTERNAL APPLICANTS Position is a pay grade 20H

Employee Type: Permanent

UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.

Other Criteria: Employer will sponsor visas for specific positions. UPS is an equal opportunity employer. UPS does not discriminate on the basis of race/color/religion/sex/national origin/veteran/disability/age/sexual orientation/gender identity or any other characteristic protected by law.

Basic Qualifications: Must be a U.S. Citizen or National of the U.S., an alien lawfully admitted for permanent residence, or an alien authorized to work in the U.S. for this employer.

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