Data Analyst

Location: Makati City, Philippines

WHAT WE OFFER

• Competitive Salary Packages
• Professional Development Opportunities
• Hybrid Work Setup
• Equipment Provided
• Day 1 HMO
• Life Insurance

POSITION OVERVIEW
The Data Analyst role in the Business Development team gives exposure to the Payreto staff who wants to build strong, practical experience in data analytics, automation, business intelligence, and applied data science. The Data Analyst will gain exposure to real business problems across Payreto’s internal units and external financial services clients, including operations, compliance, sales, marketing, productivity, quality, and performance analysis.

The ideal candidate is highly analytical, technically curious, and comfortable working with complex (or sometimes unavailable) datasets, unclear business questions, and evolving stakeholder requirements. He should have a flexible and agile mindset as he will be confronted with a lot of topics within Payreto and its clients. This role requires strong ownership and problem solving, attention to detail, and the ability to use Python and other data tools to clean, analyze, automate, and visualize data.

In this regard, he / she should be extremely engaged in learning about the business of Payreto and its clients in a deeper level and be OBSESSED WITH LEARNING IN GENERAL and is ACTION ORIENTED.

The opportunity is not for candidates who would like to have an easy job. This opportunity is for anyone who wants to be challenged, grow, and achieve expertise in the financial services space. A successful candidate who has proven to the company that he could add value will be given opportunities beyond what a normal Philippine company would give.

WHAT WILL YOU DO?
Data Extraction, Cleaning, and Processing

• Pull, extract, consolidate, and prepare data from multiple sources, systems, databases, spreadsheets, reports, and business tools
• Clean raw datasets by identifying missing values, duplicates, formatting issues, inconsistencies, and other data quality concerns.
• Use Python, spreadsheets, SQL, or other relevant tools to process, transform, and structure data for analysis.
• Validate data accuracy by reconciling information across different systems, reports, or source files.
• Maintain organized data files, documentation, and analysis outputs for repeatable use.
• Identify and escalate data integrity issues that may affect reporting accuracy, business decisions, or client deliverables.

Data Analysis and Business Reporting

• Analyze datasets to identify trends, patterns, anomalies, performance movements, and operational insights.
• Prepare recurring and ad-hoc reports for internal teams, management, and client stakeholders.
• Analyze operational, sales, marketing, compliance, productivity, quality, and client performance data.
• Detect abnormal spikes, drops, or suspicious patterns in the data and communicate these to the relevant stakeholders.
• Translate business questions into clear data analysis outputs.
• Provide data-backed recommendations to support decision-making across Payreto units.
• Summarize findings in a way that is clear, concise, and useful for both technical and non-technical audiences.

Dashboarding and Data Visualization

• Build and maintain dashboards using tools such as Power BI, Looker Studio, Google Sheets, Excel, or other visualization platforms.
• Create charts, tables, summaries, scorecards, and other visual outputs that make data easier to understand.
• Design dashboards that track key performance indicators, operational productivity, client metrics, quality results, and business outcomes.
• Ensure dashboards are accurate, readable, updated, and aligned with stakeholder needs.
• Improve existing reports and dashboards by making them more automated, scalable, and decision-oriented.

Python-Based Automation, Process Improvement, and Technical Analysis

• Use Python to automate repetitive data cleaning, reporting, reconciliation, and analysis tasks.
• Write scripts to process large datasets, combine multiple files, generate summaries, and produce recurring reports.
• Support the development of internal tools, reporting templates, or automation workflows that improve team efficiency.
• Apply basic statistical methods to support analysis, forecasting, segmentation, correlation checks, or performance measurement.
• Assist in exploratory data analysis and basic applied data science projects when needed.
• Continuously improve technical capability in Python, SQL, analytics tools, and automation methods.

Client-Facing and Stakeholder Communication 

• Communicate analysis, findings, limitations, and recommendations clearly to internal and external stakeholders.
• Ask relevant questions to clarify business objectives, report requirements, definitions, assumptions, and expected outputs.
• Set realistic expectations on timelines, data limitations, risks, and dependencies.
• Prepare clean and professional outputs that may be used in client discussions, management reports, business reviews, or internal planning.
• Explain technical work in simple business language.
• Work professionally with stakeholders from different functions, backgrounds, and levels of technical understanding.

Other Tasks

• Help promote a stronger data-driven culture within the organization.
• Support special projects assigned by the immediate supervisor or management team.
• Assist in research, analysis, automation, data validation, reporting, and process improvement initiatives.
• Take on new tools, datasets, or business topics as required by Payreto’s evolving needs.
• Join product vendor discussions on AI, Data Science, etc.
• Perform other official work as instructed by the immediate supervisor/manager.
• Recommend and proactively implement opportunities for increased departmental efficiency.
• Stay updated on industry trends, news, and techniques.
• Keep organized files and documentation.
• Extend work hours when needed.

WHAT SHOULD YOU HAVE?

• Bachelor’s degree in Business, Finance, Economics, Physics, Mathematics, Computer Science, Industrial Engineering
• 0 – 2 yrs experience in data analysis and python projects
• Must have advanced proficiency in MS Office Suite, experience in G Suite (Google), Python, Looker Studio / Power BI, Streamlit, Google App Scripts.
• Very strong communication verbal and written skills.
• Outstanding cognitive, comprehension, and strong analytical and statistical thinking skills
• Proven business acumen and has tenacity to always continue without seeing immediate success (displaying entrepreneurial qualities).
• Problem Solver
• Ability to work effectively in a team environment
• Ability to present ideas clearly and persuasively
• Excellent attention to detail and a commitment to quality.
• Ability to work independently and manage time effectively.

SHIFT SCHEDULE

• MID-SHIFT (2PM - 11PM).
• FLEXI.
• Subject to change depending on business needs.