UPS is hiring for a fresher entry level Data Scientist job in India

Position: Data Scientist

Company: UPS

Location: Chennai, India

Job Type: Permanent

Job Mode: Full-time. Onsite

Job Requisition ID: R24002030

Years of Experience: 0-3 years

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Company Description

UPS, a Fortune Global 500 Company:

• Global Leadership: Recognized as a global leader in logistics, UPS provides innovative supply chain solutions to clients worldwide.
• Diverse Operations: With a presence in over 220 countries and territories, UPS delivers more than 24.7 million packages and documents daily.
• Commitment to Innovation: Pioneering in technology and operations, UPS is committed to continuous improvement and innovation in logistics and supply chain management.
• Work Culture: UPS fosters a collaborative and dynamic work environment, encouraging employees to develop professionally and personally.
• Sustainability Focus: UPS emphasizes sustainability, aiming to minimize its environmental impact through eco-friendly initiatives and practices.

Profile Overview

Role of Data Scientist at UPS:

• Data Analysis and Model Creation: Responsible for developing and deploying advanced analytics models to derive actionable insights from large datasets.
• Collaboration: Works in conjunction with a team to meet predictive and prescriptive analytic needs using state-of-the-art machine learning tools.
• Technology Utilization: Leverages cutting-edge tools in both On-prem and Cloud environments to convert raw data into valuable insights.
• Insights and Solutions: Identifies opportunities to transition from descriptive to predictive solutions that inform decision-making and support project teams.
• Stakeholder Communication: Effectively communicates findings and recommendations to stakeholders through reports and presentations.

Responsibilities

Key Responsibilities Include:

• Data Source Identification: Identify and integrate key data sources, both internal and external, for model development.
• Pipeline Development: Create and implement data pipelines for data cleansing, transformation, and enrichment from various sources.
• Collaboration with Engineering Teams: Collaborate with data engineering teams to validate and test data and model pipelines.
• Data Design: Develop data designs based on the exploratory analysis of large datasets to uncover trends and meet business needs.
• Model Validation: Define model KPIs and conduct validation, testing, and re-training of models to ensure they meet business objectives.
• Solution Documentation: Document solutions with project documentation, process flowcharts, and clean code for reproducibility.
• Insight Presentation: Synthesize insights and present findings through clear and concise presentations and reports to stakeholders.
• Analytic Findings: Operationalize analytic findings and provide actionable recommendations.
• Best Practices: Incorporate best practices in statistical modeling, machine learning, and cloud-based AI technologies for deployment and market introduction.
• Tool Utilization: Use emerging tools and technologies, including open-source and vendor products, to support predictive and prescriptive solutions.

Qualifications

Required Skills and Experience:

• Programming Expertise: Proficient in R, SQL, Python, or other high-level languages.
• Exploratory Data Analysis (EDA): Skilled in data analysis, data engineering, and the development of advanced analytics models.
• AI and ML Platforms: Experience with platforms like VertexAI, Databricks, or Sagemaker, and familiarity with frameworks such as PyTorch, TensorFlow, and Keras.
• Problem-Solving Skills: Capable of applying models to solve small to medium-scale problems effectively.
• Analytical Skills: Strong analytical skills with meticulous attention to detail.
• Stakeholder Engagement: Ability to engage with business and executive-level stakeholders to translate business problems into analytics solutions.
• Statistical Techniques: Expertise in statistical techniques, machine learning, and operations research, with applications in business contexts.
• Data Management: Deep understanding of data management pipelines and experience in launching advanced analytics projects.
• Cloud-AI Knowledge: Demonstrated experience in Cloud-AI technologies and familiarity with both Linux/Unix and Windows environments.
• Open-Source Technologies: Experience with implementing open-source technologies and cloud services, with or without enterprise data science platforms.
• Machine Learning Knowledge: Core knowledge of AI and Machine Learning, including supervised and unsupervised learning domains.
• Programming Knowledge: Familiarity with Java or C++ is considered a plus.
• Communication Skills: Excellent oral and written communication skills, especially regarding analytical concepts and methods.
• Educational Background: Master’s degree in a quantitative field (e.g., mathematics, computer science, physics, economics, engineering, statistics) or equivalent job experience.

Any Additional Info

Additional Information:

• Workplace Commitment: UPS is committed to providing a workplace free from discrimination, harassment, and retaliation.
• Employee Type: This is a permanent role.
• Company’s Mission: UPS is dedicated to delivering excellence in global logistics and supply chain solutions, fostering a work environment that values diversity and innovation.

Please click here to apply.

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