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.
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 the wealth of data we receive each day provides the foundation which enables many of UPS' core processes.
About This Role:
Reporting to the Director of Data Science, the Lead Data Scientist will drive advanced analytics initiatives to solve some of the most interesting business problems across the UPS enterprise. As a key member of a growing global team, you will operate in a fast-paced environment and take on multiple roles. You 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 your work. You will employ tools and applications that can fast-track manual steps such as ETL, data exploration, etc. You will have the opportunity to research and experiment with innovative new techniques in machine learning, statistics, and operations research. You will have the freedom to attend conferences and training sessions, as well as collaborate with partner universities, to further your skillset. You will present in front of executive-level decision makers.
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. For those with the right background, there's an option to supervise other team members.
- Provides technical leadership and broad subject matter expertise on cutting-edge computational, quantitative, and algorithmic techniques applicable to data science
- Performs data wrangling, ETL, and data exploration tasks
- Builds predictive and prescriptive models, algorithms, and simulations
- Mentors and possibly manage junior-level and senior-level data scientists
- Curates relationships and disseminate work between cross-functional teams of data scientists, data engineers, application developers, service providers, and business analysts
- Identifies and champion new initiatives aimed at delivering value to business stakeholders
- Oversees the entire lifecycle of projects, including: scoping, design, modeling, validation, deployment
- Manages multiple work streams while proactively responding to competing demands
- Institutes standards, procedures, and guidelines for all aspects of data science practice
- Evaluates open-source and vendor-based tools, applications, platforms, frameworks and programming languages
- Master's degree in statistics, operations research, computer science, physics or related discipline
- 7+ years of industry experience applying machine learning, statistical modeling, or optimization algorithms to large data sets
- Proven track record of leading large-scale data science projects and generating actionable business results
- Expert knowledge of R or Python
- Advanced 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.)
- Extensive experience querying relational data systems for ETL and data integration tasks
- Experience working in a cloud-computing environment such as AWS, Azure, GCP, etc
- Exceptional communications skills with ability to present to technical and business audiences, including executive-level sponsors
- PhD degree
- Knowledge of any of the following: 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
- Experience using Spark/Hadoop systems for distributed analytics and data processing
- Knowledge of: H2O.ai, TensorFlow, SAS
- Proficiency in scaling and operationalizing data science models in production settings
- 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.
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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