Senior Data Scientist

Key Skills

Java Programming, Design, Python Programming, SQL, Azure, Data science techniques, Natural Language Processing (NLP), Google Cloud Platform (GCP), R Programming, Data Engineering, ETL frameworks, Text segmentation, Dimensionality reduction, VR/AR frameworks

Job Description

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.

About the Advanced Technology Group at UPS:

The UPS Advanced Technology Group is driving quantitative insights about the UPS network of today and tomorrow. Our team is comprised of individuals who are experts in data analytics, optimization, and machine learning.

About this role:

The Senior 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 and Cloud technology, to speed up work. 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.

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.

Responsibilities:

• Provide expertise on computational, quantitative, and algorithmic techniques applicable to data science
• Perform data wrangling, ETL, and data exploration tasks as necessary
• 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 multiple work streams while proactively responding to competing demands
• Evaluate open-source and vendor-based tools, such as applications, platforms, frameworks and programming languages

Minimum Qualifications:

• Master's degree in a quantitative or computational field such as statistics, operations research, computer science, physics, engineering, mathematics, economics, biology, or related discipline
• 3+ years of industry experience in a technical role
• Advanced knowledge of R or Python
• Some knowledge of the following: Generalized Linear and Non-Linear Models, Time Series Analysis, Random Forest, Gradient Boosted Machines, Neural Networks, Natural Language Processing, Unsupervised Methods (Dimensionality Reduction, Clustering, etc.)
• Experience querying relational data systems for ETL and data integration tasks (SQL for example)
• Good communications skills with ability to present to technical and business audiences
• Experience using cloud-based environments (GCP, Azure, etc.)

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
• Familiarity with scaling and operationalizing data science models in production settings
• Experience working in a cloud-computing environment such as AWS, Azure, GCP, etc
• Prior exposure to the transportation or logistics industry