500 UPS

The APAC Data and Analytics Specialist – Digital Intelligence supports the regional Digital Intelligence team in building scalable customer, campaign, and marketing analytics capabilities across Asia Pacific. This role is responsible for developing the technical foundation for Single View of Customer, integrating and transforming data from enterprise and marketing platforms, automating recurring analytical processes, and enabling reusable Power BI reporting and data models. The role uses efficient and advanced analytics to derive insights and to support customer engagement, commercial growth, and informed decision-making.

Job Responsibilities

Customer Intelligence and Single View of Customer

Translate customer and marketing business requirements into scalable data models, datasets, and analytical solutions supporting the APAC Single View of Customer.
Integrate available customer/account information, shipment and revenue performance, product or service usage, customer segmentation, and marketing engagement data into reusable customer-level analytical structures.
Support the development of relationships between UPS ID holders and account holders where data and identifiers allow, and enable analysis across relevant customer populations and sales coverage segments.
Develop approaches to retain and analyze customer history over time, including changes that may no longer be visible in current monthly source files.
Partner with Customer and Campaign Intelligence stakeholders to implement agreed customer lifecycle, campaign, and KPI definitions in analytical models and reporting solutions.

Data Integration, Automation, and Power BI

Extract, combine, transform, and validate data from enterprise data warehouses, CRM/marketing platforms, and other approved data sources using Power Query, SQL, and other appropriate tools.
Develop repeatable ETL and data preparation workflows that reduce manual effort, improve consistency, and support recurring customer, campaign, and performance analytics.
Design and maintain reusable Power BI semantic models, DAX measures, and reporting solutions rather than isolated one-off dashboards.
Improve data quality, refresh reliability, model performance, and documentation, including source-to-report logic, transformations, dependencies, and validation checks.
Support the prioritized migration of Microsoft Access and spreadsheet-based analytical processes toward more scalable and maintainable solutions.
Use Python where data scale, complexity, automation, or analytical requirements make it appropriate.

Analytics Enablement and Team Capability

Enable standardized campaign analytics, customer segmentation, lifecycle analysis, reactivation, cross-sell, and customer growth analysis through reliable datasets and analytical tools.
Support customer-level analytics for strategic programs, including preparation of analytical views and measurement datasets.
Progressively support advanced analytical use cases such as clustering, propensity analysis, at-risk identification, experimentation, and recommendation analytics as the data foundation matures.
Provide technical guidance and reusable components that enable other Digital Intelligence team members to develop and maintain their own Power BI reporting and analysis.
Partner with regional, country, Corporate, IT, and external vendor stakeholders as required to support scalable analytics solutions and productionization.

Job Requirements

Possess a Bachelor's Degree in Business Analytics, Data Analytics, Marketing, Data Science, Information Systems, Computer Science, Statistics, Engineering, or a related discipline.
2–5 years of relevant experience in data analytics, business intelligence, data engineering, marketing analytics, or a related function. Candidates with strong hands-on project experience may also be considered.
Strong hands-on experience with Power BI and Power Query, including data modeling and dashboard/report development. Portfolio or dashboard samples are highly encouraged.
Strong SQL skills and experience working with relational databases, enterprise data warehouses, or large transactional datasets.
Sound understanding of data modeling, ETL/data preparation, data validation, and combining multiple data sources at different levels of detail.
Strong analytical and structured problem-solving skills, with the ability to translate business questions into practical data and BI solutions.
Effective communication skills, with the ability to present technical insights to business stakeholders.
Experience with Python for data manipulation, automation, or analytics is strongly preferred. Familiarity with DAX, CRM/marketing data, Oracle, historical/snapshot data, or campaign measurement is an advantage.
Attention to detail and ability to manage multiple priorities in a fast-paced, matrixed, regional environment.
Collaborative, proactive, adaptable, and willing to learn, with a strong sense of ownership and accountability.

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UPS

APAC Data and Analytics Specialist Digital Intelligence