Data Analyst I

RELX; Quezon City; On-site; PHP 420,000 - 700,000; Full time

Job summary

RELX is seeking a Data Analyst to collaborate with teams to receive, analyze, and manipulate data while building processes and tools to help customers make informed decisions. You will learn various solutions and work with cloud and PC-based tools to support analytics products for internal projects and external customers.

As part of the analytics ecosystem, you will work with modeling partners to provide data insights and contribute to data-driven decisions across projects, maintaining data

Qualifications

• Bachelor’s degree required in a relevant field.
• Fresh graduates with internship in data analytics are eligible.
• 1–3 years of data analytics or data engineering experience preferred.
• Proficiency in Python and SQL; knowledge of Azure or cloud tools helpful.
• Experience with Git or other version control systems; strong Excel skills.
• Able to communicate analytical results to non-technical audiences.

Responsibilities

• Develop data-driven testing methodologies using available data assets.
• Clarify test objectives and data requirements with stakeholders.
• Analyze client data for preparation and identify data quality issues.
• Design, test and automate data processing and reporting workflows.
• Run database queries to extract/aggregate data for modeling and reporting.
• Create and maintain Python or Power BI reporting tools for insights.
• Enforce data quality testing best practices and document results.

Skills

Analytical thinking

Communication

Problem solving

Team collaboration

Education

Bachelor's degree

Tools

Python

SQL

Power BI

Git

Azure

Excel

Job description

Job Summary

As an Analyst, you will be collaborating with teams to receive, analyze and manipulate data, along with creating processes and tools to assist customers in making informed decisions about their data. You will learn about different solutions and use a variety of Cloud and PC based tools. The Data Analyst will be helping to support analytics products for both internal projects and external customers. We also work alongside our Analytic Consulting and Modeling partners to provide data and product insights.

Accountabilities

• Develops data-driven testing methodologies using data assets.


• Clarifies and/or enhancing stakeholder understanding of test objectives and the data required to support the test.


• Analyzes client data to prepare for analysis. Identifies data quality concerns and opportunities (i.e. performance indicators, scores, approval/declination indicators, etc.) and clearly communicates these concerns to stakeholders along with suggestions for preventing these issues closer to project initiation.


• Designing, testing, and/or executing automated file processing and data reporting workflows.


• Executing database queries to extract and aggregate data assets into attributes and scores that are used for predictive modeling, reporting, and analysis.


• Creating and enhancing the code and tools that support data processes. Tools are easily usable by a wide audience, including teams outside of Data Science.


• Creating and enhancing Python or Power BI-based reporting tools that allow team members to gain insights about LexisNexis data assets.


• Enforcing data quality testing best practices.


• Performing all other duties as assigned.

Qualifications

• Bachelor’s degree holder


• Open to fresh graduates with relevant internship or practicum, experience related to data analytics, data science, or data engineering.


• 1–3 years of experience in data manipulation, data cleansing, and/or data modeling (or equivalent internship experience) demonstrating the core analytical skill set required to support project requests.


• Experience with at least one general purpose programming or analytics language (e.g., Python, Spark, or R).


• Working knowledge of SQL and database technologies.


• Experience using Git or other version control systems.


• Familiarity with cloud based tools and platforms (e.g., Microsoft Azure or equivalent).


• Proven ability to manipulate, cleanse, match, and merge large datasets.


• Strong analytical and problem solving skills, with attention to data verification and validation.


• Basic proficiency in Microsoft Excel and Word.


• Comfortable working in a fast‑paced, collaborative environment.


• Ability to quickly learn new tools, technologies, and programming languages.


• Strong attention to detail, organization, and documentation.


• Excellent written and verbal communication skills, with the ability to explain analytical results to non‑technical audiences.


• Ability to quickly learn and apply enterprise AI tools and technologies to support technical workflows and business objectives.

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