UPS Job - 39576644 | CareerArc
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Company: UPS
Location: Mahwah, NJ
Career Level: Associate
Industries: Transportation, Logistics, Trucking


Lead Data Scientist

We're the obstacle overcomers, the problem get-arounders. From figuring it out to getting it done… our innovative culture demands “yes and how!” We are UPS. We are the United Problem Solvers. We Deliver What Matters.

About Information Management at UPS Technology:

Our Information Management teams are responsible for designing and supporting data solutions to meet UPS's rapidly changing business needs. Our team is comprised of individuals who are experts in data management, compliance and governance. We ensure quality, completeness, availability, protection, understanding and effective use of our data assets. Our ability to organize and design data provides the foundation which enables many of UPS' core processes.

About this role:

The Lead Data Scientist will leverage advanced analytics to solve some of the most interesting business problems across the UPS enterprise. As a key member of a growing global team, he/she will operate in a fast-paced environment and take on multiple roles. He/she will have access to large volumes of structured and unstructured data as well as the ability to allocate vast computing resources, including GPU's, to speed up work. The candidate will employ tools and applications that can fast-track manual steps such as ETL, data exploration, etc. He/she will have the opportunity to research and experiment with innovative new techniques in machine learning, statistics, and operations research. The candidate will have the freedom to attend conferences and training sessions, and collaborate with partner universities, to further build their skillset. The selected candidate will both serve in an individual contributor role, with a focus on hands-on technical work, and be asked to take on non-technical assignments such as business requirements gathering or vendor evaluation.

This role requires the ability to balance between hands-on work and delegating to others. Although there's a strong technical focus, you must be comfortable taking on non-technical assignments such as project management. You will serve as an individual contributor or as a lead depending on assignment.


  • Provide expertise on computational, quantitative, and algorithmic techniques applicable to data science
  • Perform data wrangling, ETL, and data exploration tasks
  • Build predictive and prescriptive models, algorithms, and simulations
  • Mentor junior-level data scientists
  • Collaborate with cross-functional teams of data scientists, data engineers, application developers, etc. to deliver measurable outcomes
  • Identify and champion new initiatives aimed at delivering “Wildly Important” value to business stakeholders
  • Manage and lead multiple work streams while proactively responding to competing demands
  • Evaluate open-source and vendor-based tools, such as applications, platforms, frameworks and programming languages
  • Lead MLOps initiatives across the enterprise by providing guidelines based on best-practices on how applications can solution data and analytics initiatives
  • Design and implement models within apps or software using a data science solution
  • Optimize models with data engineering techniques like data storage and OOP improvements

Minimum Qualifications:

  • Master's degree in a quantitative or computational field such as statistics, computer science, physics, engineering, mathematics, economics, biology, operations research, or related discipline
  • 5+ years of industry experience in a technical role by implementing solutions and applications at an enterprise level in different functions like Pricing, Marketing, Churn, Customer Experience, Human Capital Transformation & Optimization
  • Advanced knowledge of Python and/or R, and SQL
  • Experience using Spark/Hadoop systems for distributed analytics and data processing
  • Deep knowledge of the following: Generalized Linear and Non-Linear Models, Time Series Analysis, Random Forest, Gradient Boosted Machines, Neural Networks, Unsupervised Methods (Dimensionality Reduction, Clustering, etc.)
  • Good communications skills with ability to present to technical and business audiences

Preferred Qualifications:

  • PHD degree
  • Knowledge of and experience with any of the following: Data Engineering, Natural Language Processing & Text Mining, Experimental Design, Computer Vision & Image Processing, Bayesian Networks, Reinforcement Learning, Collaborative Filtering, Network/Graph Mining, Combinatorial Optimization, Linear & Mixed-Integer Programming, Discrete-Event & Stochastic Simulation
  • Knowledge of:, TensorFlow, SAS
  • Familiarity with scaling and operationalizing data science models in production settings
  • Experience working in multi-cloud computing environments such as AWS, Azure, GCP, etc
  • Prior exposure to the transportation or logistics industry

This position offers an exceptional opportunity to work for a Fortune 50 industry leader. If you are selected, you will join our dynamic technology team in making a difference to our business and customers. Do you think you have what it takes? Prove it! At UPS, ambition knows no time zone.


  • 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
  • Now or in the future UPS employment sponsorship, such as H1B, TN, J-1, F-1, etc., is not needed in order to start or continue temporary or permanent employment with UPS.
  • Master's degree in a quantitative or computational field such as statistics, operations research, computer science, physics, engineering, mathematics, economics, or related discipline

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.

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

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