The UPS Data Scientist interview guide, interview questions, salary data, and interview experiences.

UPS Data Scientist Interview Guide

Getting ready for an Data Scientist interview at UPS? The UPS Data Scientist interview span across 10 to 12 different question topics. In preparing for the interview:
<ul>
<li>Know what skills are necessary for UPS Data Scientist roles.</li>
<li>Gain insights into the Data Scientist interview process at UPS.</li>
<li>Practice real UPS Data Scientist interview questions.</li>
</ul>
Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the UPS Data Scientist interview.


Getting ready for an Data Scientist interview at UPS? The UPS Data Scientist interview span across 10 to 12 different question topics. In preparing for the interview:

- Know what skills are necessary for UPS Data Scientist roles.
- Gain insights into the Data Scientist interview process at UPS.
- Practice real UPS Data Scientist interview questions.

Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the UPS Data Scientist interview.
        

Overview

UPS Data Scientist Salary

We've gathered this data from parsing thousands of interview experiences sourced from members.

We've gathered this data from parsing thousands of interview experiences sourced from members.

Python

Machine Learning

Product Metrics

A/B Testing

Analytics

Statistics

Probability

Algorithms

UPS Data Scientist Interview Process

You work at a freight shipping company with a large fleet of trucks. These trucks are based around the nation, with a mix of Mercedes and BMW models represented. The location of each truck that your company owns is stored as <code>(x,y)</code> coordinates in your database.

Given a list of locations that your trucks are stored at, return the top location <code>(x,y)</code> for each model of truck (Mercedes or BMW).

You can assume that there is one location with the most model of a truck, e.g. there will not be any locations that are tied for most BMWs stored.

Example:

Input:

<pre tabindex="0" class="chroma"><code>truck_locations = [{
 &#34;model&#34; : &#34;BMW&#34;,
 &#34;location&#34; : (1,2)
 },
 {
 &#34;model&#34; : &#34;Mercedes&#34;,
 &#34;location&#34; : (2,3)
 },
 {
 &#34;model&#34; : &#34;Mercedes&#34;,
 &#34;location&#34; : (2,2)
 },
 {
 &#34;model&#34; : &#34;Mercedes&#34;,
 &#34;location&#34; : (2,3)
 },
 {
 &#34;model&#34; : &#34;BMW&#34;,
 &#34;location&#34; = (1,2)
 },
 {
 &#34;model&#34; : &#34;BMW&#34;,
 &#34;location&#34; : (3,3)
 }
 ]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def truck_frequent_location(truck_locations) -&gt; { 
 &#34;Mercedes&#34; : (2,3), 
 &#34;BMW&#34; : (1,2) 
 }
}
</code></pre>

Explanation:

Mercedes repeated two times at location <code>(2,3)</code> and one time at the location <code>(2,2)</code>, so <code>(2,3)</code> is our most stored Mercedes location.

BMW repeated two times at location <code>(1,2)</code> and one time at the location <code>(3,3)</code>, so <code>(1,2)</code> is our most stored BMW location.

Given a list of locations that your trucks are stored at, return the top location for each model of truck (Mercedes or BMW).

Location Frequency

Let’s say that you’re working on a job recommendation engine. You have access to all user Linkedin profiles, a list of jobs each user applied to, and answers to questions that the user filled in about their job search.

Using this information, how would you build a job recommendation feed?

What problem can arise in job recommendation systems with regard to initial recommendations?

What problem can arise in job recommendation systems with regard to initial recommendations?

Job Recommendation

Let’s say you are designing a marketplace for your website.

Selling firearms is prohibited by your website’s Terms of Service Agreement (not to mention the laws of your country). To this end, you want to create a system that can automatically detect if a listing on the marketplace is selling a gun.

How would you go about doing this?

While designing a system to detect firearms listings on a marketplace website, what metrics could be used to minimize both false positives and false negatives?

While designing a system to detect firearms listings on a marketplace website, what metrics could be used to minimize both false positives and false negatives?

Detecting Firearm Sales

How would you build a model to detect if a post on a marketplace is talking about selling a gun?

UPS Data Scientist Interview Questions

Before you apply to a job, select your language preference from the options available at the top right of this page.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 tomorrowpeople 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:Internal Job Grade- 20GThis position is responsible for creating and implementing advanced analytics models and solutions to yield predictive and prescriptive insights from large volumes of structured and unstructured data. This position works with a team responsible for the research and implementation of predictive requirements by leveraging industry standard machine learning and data visualization tools to draw insights that empower confident decisions and product creation. The incumbent leverages emerging tools and technologies available in On-prem and Cloud environments. The incumbent utilizes industry standard Machine learning and Data visualization tools to transform data and analytics requirements into predictive solutions and provide data literacy on a range of machine learning systems at UPS. This position identifies opportunities for driving descriptive to predictive and prescriptive solutions, which become inputs to department and project teams on their decisions supporting projects.Responsibilities<ul><li><h2>Defines key data sources from UPS and external sources to deliver models.</h2></li><li><h2>Develops and implements pipelines that facilitates data cleansing, data transformations, data enrichments from multiple sources (internal and external) that serves as inputs for data and analytics systems. For larger teams, works with data engineering teams to validate and test data and model pipelines identified during proof of concepts.</h2></li><li><h2>Develops data design based on the exploratory analysis of large amounts of data to discover trends and patterns that meet stated business needs.</h2></li><li><h2>Defines model KPI expectations and validation, testing, and re-training of existing models to meet business objectives.</h2></li></ul><ul><li><h2>Defines key data sources from UPS and external sources to deliver models.</h2></li><li><h2>Develops and implements pipelines that facilitates data cleansing, data transformations, data enrichments from multiple sources (internal and external) that serves as inputs for data and analytics systems. For larger teams, works with data engineering teams to validate and test data and model pipelines identified during proof of concepts.</h2></li><li><h2>Develops data design based on the exploratory analysis of large amounts of data to discover trends and patterns that meet stated business needs.</h2></li><li><h2>Defines model KPI expectations and validation, testing, and re-training of existing models to meet business objectives.</h2></li><li><h2>Reviews and creates repeatable solutions through written project documentation, process flowcharts, logs, and commented clean code to produce datasets that can be used in analytics and/or predictive modeling.</h2></li><li><h2>Synthesizes insights and documents findings through clear and concise presentations and reports to stakeholders.</h2></li><li><h2>Works with the team to present operationalized analytic findings and provide recommendations.</h2></li><li><h2>Incorporates best practices on the use of statistical modeling, machine learning algorithms, distributed computing, cloud-based AI technologies and run time performance tuning with the goal of deployment and market introduction.</h2></li><li><h2>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.</h2></li></ul>Qualifications<ul><li><h2>Bachelors degree with 2+ years of experience</h2></li><li><h2>Strong analytical skills, attention to detail. </h2></li><li><h2>Able to engage key business and executive-level stakeholders to translate business problems to high level analytics solution approach.</h2></li><li><h2>Expertise with statistical techniques, machine learning or operations research and their application in business applications, especially libraries used in data science like TensorFlow, PyTorch, Scikit-learn, etc.</h2></li><li><h2>Expertise in R, SQL, Python </h2></li><li><h2>Deep understanding of data management pipelines and experience in launching moderate scale advanced analytics projects in production at scale</h2></li><li><h2>Experience with LLMs is a plus, but a well-rounded ML/deep learning background is key</h2></li><li><h2>Demonstrated experience in Cloud-AI technologies and knowledge of environments both in Linux/Unix and Windows. </h2></li><li><h2>Experience implementing open-source technologies and cloud services; with or without the use of enterprise data science platforms, familiarity with big data technologies such as Spark, or similar platforms</h2></li><li><h2>Solid oral and written communication skills, especially around analytical concepts and methods. Able to communicate data through a story framework to convey data-driven results to technical and non-technical audience.</h2></li></ul><h3>The position is based in Atlanta, Georgia and will require commuting to office. Employer will not sponsor a visa for this position. Must be currently in the same geographic location as the job or willing to relocate yourself.</h3>Employee Type:PermanentUPS 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.

Before you apply to a job, select your language preference from the options available at the top right of this page. 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 conducts the design, build, test, and delivery of Machine Learning (ML) models and software components that solve challenging business problems for the organization, working in collaboration with the Business, Product, Architecture, Engineering, and Data Science teams This position supervises and engages in assessment and analysis of large-scale data sources of structured and unstructured data (internal and external) to uncover opportunities for ML and Artificial Intelligence (AI) automation, predictive methods, and quantitative modeling across the organization. This position designs trials and tests to measure the success of software and systems, and works with teams, or individually, to implement ML/AI models for production scale. RESPONSIBILITIES •Transforms and develops data science prototypes into ML systems using appropriate datasets and data representation models with moderate complexity. •Researches and implements appropriate ML algorithms and tools that create new systems and processes powered with ML and AI tools and techniques according to business requirements •Designs and implements workflows and analysis tools to streamline the development of new ML models at scale both in batch and streaming mode. •Creates and evolves ML models and software that enable state-of-the-art intelligent systems using best practices in all aspects of engineering and modeling lifecycles. •Extends existing ML libraries and frameworks with the developments in the Data Science and ML field for enterprise use. •Establishes, configures, and supports scalable cloud components that serve prediction model transactions •Integrates data from authoritative internal and external sources to form the foundation of a new Data Product that would deliver insights that supports business outcomes that is necessary for ML systems. •Collaborates with skilled Designers, Architects, Software Engineers, Data Scientists and Data Engineers to deliver ML products and systems for the organization. QUALIFICATIONS Requirements: •Experience designing and building large/data-intensive solutions using distributed computing within a multi-line business environment. •Knowledgeable in Machine Learning and Artificial Intelligence frameworks (i.e., Keras, PyTorch), libraries (i.e., scikit-learn), and tools and Cloud-AI technologies that aid in streamlining the development of machine learning or AI systems. •Strong experience in establishing and configuring scalable and cost-effective end to end solution design pattern components to support the serving of batch and live streaming prediction model transactions. •Experience in developing and implementing Machine Learning models such as: Classification/Regression Models, NLP models, and Deep Learning models; with a focus on productionizing those models into product features. •Experience deploying highly scalable software, scalable feature pipeline and model optimization that is supporting millions of transactions and/or substantial number of users. •Experience in creating products and services that leverages best practices around software development lifecycle (SDLM), Agile development and cloud technology. •Solid understanding of statistics such as forecasting, time series, hypothesis testing, classification, clustering, or regression analysis, and how to apply that knowledge in understanding and evaluating Machine Learning models. •Advanced math skills in Linear Algebra, Bayesian Statistics, Group Theory and Probability. •Works collaboratively with management, and, in a technical and cross-functional context. •Strong written and verbal communication •Possesses creative and critical thinking skills. •Bachelors' (BS/BA) degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Preferred skills/expectations: <ul><li>Masters (MS/ME) degree in a quantitative discipline such as engineering, computer science, data science, bioinformatics, statistics, mathematics, international equivalent, or equivalent job experience </li><li>Experience designing and building data-intensive solutions using distributed computing within a multi-line business environment. </li><li>Experience in establishing and configuring scalable and cost-effective end to end solution design pattern components to support the serving of batch and live streaming prediction model transactions in the Google Cloud Platform (GCP). </li><li>Experience with scalable data processing, feature development, and model optimization. </li><li>Knowledgeable in software development lifecycle (SDLM), Agile development practices and cloud technology infrastructures and patterns related to product development. </li><li>Advanced math skills in Linear Algebra, Bayesian Statistics, Group Theory. </li><li>Works collaboratively, both in a technical and cross-functional context. </li><li>Prior experience within a UPS operational context (e.g., air gateways, hubs, ground facilities) that can aid with understanding business domain problems. </li></ul> 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.

Before you apply to a job, select your language preference from the options available at the top right of this page.
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:
TITLE: MACHINE LEARNING ENGINEER The Machine Learning Engineer position participates in the support, maintenance, and monitoring of Machine Learning (ML) models and software components that solve challenging business problems for the organization, working in collaboration with the Business, Product, Architecture, Engineering, and Data Science teams.This position participates in assessment and analysis of large-scale data sources of structured and unstructured data (internal and external) to uncover opportunities for ML and Artificial Intelligence (AI) automation. This position works with teams, or individually, to debug, develop minor enhancements, and complete other tasks related to ML/AI environments. RESPONSIBILITIES
Manage machine learning models in production environments, ensuring smooth integration with existing systems
Monitor model performance using established metrics (accuracy, precision, recall, F1 score, etc.) and identify potential issues like performance degradation, drift, or bias
Participate in the response and resolution of production incidents promptly, minimizing downtime and impact on business operations
Collaborate with stakeholders (data scientists, software engineers, operations) to diagnose and fix problems
Maintain documentation for deployed models, including deployment logs, monitoring dashboards, and troubleshooting procedures
Ensure model compatibility with new software versions and infrastructure changes.
Archive and manage different model versions for auditability and rollback capabilities.
Analyze logs, error messages, and other data to diagnose model issues.
Utilize debugging tools and techniques specific to machine learning (profiling, feature importance analysis, anomaly detection).
Reproduce and isolate issues in test environments before fixing them in production.
Document bug fixes and lessons learned to improve future model development and maintenance.
Analyze monitoring data proactively to identify trends and potential issues before they impact production.
Stay up-to-date on new monitoring tools and techniques for machine learning systems.
Report on model performance and health to stakeholders regularly.
Stay up-to-date on advances in machine learning and best practices for production usage.
Contribute to documentation and knowledge sharing within the team. QUALIFICATIONS
Primary:
Demonstrated proficiency in Python, SQL, and cloud platforms such as GCP, AWS, or Azure.
Experience in DevOps practices for supporting and maintaining applications and products driven by Machine Learning (ML) and Artificial Intelligence (AI).
Expertise in developing and optimizing ML pipelines.
Understanding and experience in scaling solutions for ML and AI applications.
Demonstrate experience in various ML frameworks such as Python, Scala or Java for debugging and developing minor enhancements to models.
Proficiency in deploying and managing models using Kubernetes
Experience in supporting products with capabilities including Deep Learning, Supervised, and Unsupervised techniques.
Familiarity with implementing solutions using Python, Scala, or Java.
Ability to utilize visualization tools for model monitoring and management in production.
Experience in deploying and managing machine learning models using containerization tools such as Kubernetes, Docker, Fargate, etc.
Documentation and communication skills for technical and non-technical stakeholders.
Strong investigative and troubleshooting skills with regards to ML Pipelines
Excellent written and verbal communication skills
Bachelor’s degree in Computer Science or related discipline, or the equivalent in education and work experience
Secondary:
Comfortable working with data scientists, data engineers, product owners and architects
Background in Agile/Kanban development methodologies.
Experience working within Agile Frameworks for ML and AI projects. Employee Type: Permanent
UPS is committed to providing a workplace free of discrimination, harassment, and retaliation. #J-18808-Ljbffr

Before you apply to a job, select your language preference from the options available at the top right of this page. 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: Product Manager Plans, develops, and manages the organization's information software, applications, systems, and networks. Ensures UPS's business needs are met through continual upgrades and development of new technical solutions. Analyzes business systems, processes, and related data to determine how solutions can be engineered to provided new or improved business capabilities and/or processes. Acts as a member of a product team responsible for the translation of business terms and processes into technical requirements, specifications, and/or acceptance criteria. Function as a proxy product owner and subject matter expert for their various business domains. Core competencies included requirements engineering, requirements elicitation, processes modeling, and workshop facilitation. Prepares communications and makes presentations on system enhancements and/or alternatives. Provides specific functional expertise that is theoretical and conceptual in nature. This expertise is typically acquired through a combination of university education and experience within a field. May have responsibility for supervising others in the capacity of a "player coach" but primary focus is individual expertise. Particularly at higher levels, sophisticated subject matter expertise is a requirement for success. Applies working knowledge and experience in own job discipline. Continues to broaden capabilities and understanding of the company, processes and customers. Solves problems in straightforward situations by analyzing possible solutions using experience, judgment, and precedents. Impacts quality of own work and the work of others on the team. Performs a range of assignments with a moderate level of guidance and direction. Strategy Development and Implementation • Analyzes financial and market situations and participates in the creation of a business case or part of a business strategy. • Applies/integrates the business strategy to work of own team, understanding the main goals of the organization. • Analyzes data to provide information to stakeholders on strategic issues; provides information to facilitate the calculation of the ROI. Stakeholder Engagement Identifies and manages key business partner relationships, listens to and understands their needs and expectations, maintains open two-way communication and delivers value to business partner. Maintains, facilitates, and improves upon those relationships and demonstrates accountability for results. Develops trust and influence among key business partners. Is available and consistently communicates with business partners to reach desired goals in a timely manner, showing flexibility when needed. Process Improvement • Assesses bottlenecks in work processes within teams to streamline and simplify workflow. • Coordinates with team members to execute new ideas or approaches and achieve process improvement goals. • Compiles data and analyzes the impact of process changes. Technical Communication/Presentation • Confirms comprehension and understanding of complex information (e.g., legal, operational risk, and regulatory data) by correctly and clearly answering routine questions. • Creates clear, concise and organized communication materials (e.g., policies & procedures, guidelines, presentations, messages). • Considers and understands the audience's specific needs and comprehension level to determine the most appropriate message and delivery method, limiting or explaining technical language. Building a Business Case • Articulates the presenting business issue impacting own team and helps develop the rationale for addressing it (e.g., impact on customer satisfaction scores or team revenues). • Assists in the identification and analysis (e.g., cost/benefit, risk) of potential solutions to address the business need. • Helps determine the recommended solution, documenting the business case for change and sharing with team leadership. Project Management • Develops project plans, defines timeframe, and prioritizes tasks to achieve project milestones and deliver intended objectives. • Identifies the type of resources required to support a project, and makes recommendations for specific people, technology, partners, etc. • Monitors progress to meet project milestones, timelines, specifications and requirements. Qualifications: <ul><li> Extensive experience of programming concepts, software development lifecycle (SDLC) and methodologies (Agile, Scrum, Waterfall) </li><li> Exceptional skills to create clear and concise technical documentation, requirements, and user stories </li> <li>Ability to define Product Vision and create and manage Product Roadmap </li><li> Ability to write clear technical specifications and user guides </li><li> Experience with project management and collaboration tools like JIRA, ADO, Rally </li><li> Proficiency in using tools like SQL, Excel, and data visualization tools </li><li> Knowledge of Salesforce </li><li> Understanding of QA processes, including manual and automated testing </li><li> Excellent written and verbal communication skills </li><li> Bachelor's Degree or International equivalent in Computer Science, Information Systems, Mathematics, Statistics, or related field - Preferred </li><li> Bachelor's Degree or International equivalent in Computer Science, Information Systems, Mathematics, Statistics or related field - Preferred </li> </ul> 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.

Before you apply to a job, select your language preference from the options available at the top right of this page. 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 conducts the design, build, test, and delivery of Machine Learning (ML) models and software components that solve challenging business problems for the organization, working in collaboration with the Business, Product, Architecture, Engineering, and Data Science teams This position supervises and engages in assessment and analysis of large-scale data sources of structured and unstructured data (internal and external) to uncover opportunities for ML and Artificial Intelligence (AI) automation, predictive methods, and quantitative modeling across the organization. This position designs trials and tests to measure the success of software and systems, and works with teams, or individually, to implement ML/AI models for production scale. RESPONSIBILITIES • Transforms and develops data science prototypes into ML systems using appropriate datasets and data representation models with moderate complexity. • Researches and implements appropriate ML algorithms and tools that create new systems and processes powered with ML and AI tools and techniques according to business requirements • Designs and implements workflows and analysis tools to streamline the development of new ML models at scale both in batch and streaming mode. • Creates and evolves ML models and software that enable state-of-the-art intelligent systems using best practices in all aspects of engineering and modeling lifecycles. • Extends existing ML libraries and frameworks with the developments in the Data Science and ML field for enterprise use. • Establishes, configures, and supports scalable cloud components that serve prediction model transactions • Integrates data from authoritative internal and external sources to form the foundation of a new Data Product that would deliver insights that supports business outcomes that is necessary for ML systems. • Collaborates with skilled Designers, Architects, Software Engineers, Data Scientists and Data Engineers to deliver ML products and systems for the organization. QUALIFICATIONS Requirements: • Experience designing and building large/data-intensive solutions using distributed computing within a multi-line business environment. • Knowledgeable in Machine Learning and Artificial Intelligence frameworks (i.e., Keras, PyTorch), libraries (i.e., scikit-learn), and tools and Cloud-AI technologies that aid in streamlining the development of machine learning or AI systems. • Strong experience in establishing and configuring scalable and cost-effective end to end solution design pattern components to support the serving of batch and live streaming prediction model transactions. • Experience in developing and implementing Machine Learning models such as: Classification/Regression Models, NLP models, and Deep Learning models; with a focus on productionizing those models into product features. • Experience deploying highly scalable software, scalable feature pipeline and model optimization that is supporting millions of transactions and/or substantial number of users. • Experience in creating products and services that leverages best practices around software development lifecycle (SDLM), Agile development and cloud technology. • Solid understanding of statistics such as forecasting, time series, hypothesis testing, classification, clustering, or regression analysis, and how to apply that knowledge in understanding and evaluating Machine Learning models. • Advanced math skills in Linear Algebra, Bayesian Statistics, Group Theory and Probability. • Works collaboratively with management, and, in a technical and cross-functional context. • Strong written and verbal communication • Possesses creative and critical thinking skills. • Bachelors' (BS/BA) degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Preferred skills/expectations: <ul><li> Masters (MS/ME) degree in a quantitative discipline such as engineering, computer science, data science, bioinformatics, statistics, mathematics, international equivalent, or equivalent job experience </li><li> Experience designing and building data-intensive solutions using distributed computing within a multi-line business environment. </li><li> Experience in establishing and configuring scalable and cost-effective end to end solution design pattern components to support the serving of batch and live streaming prediction model transactions in the Google Cloud Platform (GCP). </li><li> Experience with scalable data processing, feature development, and model optimization. </li><li> Knowledgeable in software development lifecycle (SDLM), Agile development practices and cloud technology infrastructures and patterns related to product development. </li><li> Advanced math skills in Linear Algebra, Bayesian Statistics, Group Theory. </li><li> Works collaboratively, both in a technical and cross-functional context. </li><li> Prior experience within a UPS operational context (e.g., air gateways, hubs, ground facilities) that can aid with understanding business domain problems. </li> </ul> 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.

UPS Data Scientist Interview Guide

Overview

UPS Data Scientist Salary

UPS Data Scientist Interview Process

UPS Data Scientist Interview Questions

UPS Data Scientist Jobs