Website UPS
Data Scientist – UPS (United Parcel Service)
Company: United Parcel Service (UPS)
Role Title: Data Scientist
Location: Chennai, Tamil Nadu, India
Work Mode: On-Site / Hybrid
Employment Type: Full-Time (en CDI / Permanent)
Educational Requirement: Master’s Degree in a quantitative discipline (Computer Science, Mathematics,Statistics, Physics, Economics, Operations Research, Engineering, or quantitative social science) or equivalent practical experience
Core Tool Stack: Python, R, SQL, Exploratory Data Analysis (EDA), Data Pipelines, Cloud AI Platforms (VertexAI, Databricks, SageMaker), ML Frameworks (PyTorch, TensorFlow, Keras)
Operating Systems & Languages: Linux/Unix, Windows, C++/Java (Plus)
About UPS
United Parcel Service (UPS) is one of the world’s largest logistics and supply chain management companies,operating in over 220 countries and territories. Fortune 500 industry leader UPS combines global transportation infrastructure with advanced cloud technology, predictive machine learning, and operational research to optimize package flow, route scheduling, supply chain resilience, and global trade operations.UPS’s Technology Center in Chennai builds core data engineering pipelines, machine learning models, and cloud analytics microservices supporting global logistics execution.
Role Overview
UPS is recruiting an experienced Data Scientist to join its advanced analytics and machine learning team in Chennai.
In this predictive analytics role, you will convert complex, high-volume structured and unstructured logistics data into predictive and prescriptive models. You will partner with business leads and data engineering teams to build automated data transformation pipelines, train machine learning models across cloud platforms (Databricks, VertexAI, or SageMaker), monitor model KPIs, and deliver data stories that optimize supply chain decision-making.
Key Responsibilities
Data Pipeline Engineering & Exploratory Analysis
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Data Ingestion & Transformation: Define key internal and external data sources; build data pipelines for cleansing, transforming, and enriching datasets to feed analytics models.
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Exploratory Analysis & Data Design: Conduct thorough exploratory data analysis (EDA) across massive logistics datasets to uncover underlying operational patterns and design analytical feature sets.
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Collaboration with Data Engineering: Partner with data engineers to test, validate, and scale proof-of-concept model pipelines into robust production workflows.
Machine Learning Development & Model Lifecycle
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Predictive & Prescriptive Modeling: Design, implement, and tune machine learning algorithms (supervised and unsupervised learning) to address operational logistics challenges.
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Model Evaluation & Re-training: Establish target Model KPIs, evaluate performance metrics, and build repeatable mechanisms for re-training models in production.
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Cloud AI Implementation: Deploy machine learning solutions leveraging cloud platforms (Databricks, Google Cloud VertexAI, AWS SageMaker) and open-source frameworks (PyTorch, TensorFlow, Keras).
Stakeholder Engagement & Storytelling
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Data Storytelling: Synthesize statistical findings into structured presentations, flowcharts, and clear reports to convey data insights to executive and technical audiences.
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Documentation & Governance: Maintain clean, commented codebases, process flowcharts, and project logs to deliver repeatable data science solutions across enterprise teams.
Candidate Qualifications & Requirements
Required Technical Skills & Qualifications
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Education: Master’s Degree in a quantitative field (Mathematics, Computer Science, Statistics, Physics,Economics, Operations Research, or Engineering) or equivalent practical experience.
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Programming Mastery: Strong hands-on coding proficiency in Python, R, and SQL.
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Cloud & ML Ecosystem: Experience developing and deploying machine learning models on platforms like Databricks, VertexAI, or SageMaker using PyTorch, TensorFlow, or Keras.
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Statistical Foundations: Deep expertise in statistical modeling, machine learning techniques, and operations research applied to medium/large-scale business problems.
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OS & Cloud Knowledge: Demonstrated experience with Cloud-AI technologies and navigating both Linux/Unix and Windows environments.
Behavioral & Communication Competencies
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Excellent written and oral communication skills, with a proven ability to translate complex business problems into structured analytics solutions.
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Meticulous attention to detail and strong analytical problem-solving skills.
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Ability to present operationalized data findings and clear recommendations to business executives.
Good-to-Have Skills
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Familiarity with compiled programming languages such as Java or C++.
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Direct experience in logistics, route optimization, or supply chain data analytics.
Role Summary
| Attribute | Details |
| Job Title | Data Scientist |
| Company | UPS (United Parcel Service) |
| Location | Chennai, Tamil Nadu, India |
| Education | Master’s Degree in Quantitative Discipline (CS, Math, Stats, OR, Physics, Economics) |
| Primary Skill Stack | Python, R, SQL, PyTorch/TensorFlow, Databricks, VertexAI/SageMaker, EDA, Pipeline Engineering |
| Secondary Skill Stack | Linux/Unix, Windows, Java/C++ (Plus), Operations Research, Data Storytelling |
| Core Impact | Logistics Optimization, Supply Chain Forecasting, Predictive & Prescriptive Cloud AI Models |
