Business Intelligence & Data Science Associate

Meralco Group; Pasig; On-site; PHP 600,000 - 900,000; Full time

Job summary

Meralco Group seeks a Business Intelligence and Data Science Associate to design, implement, and operationalize advanced data models across descriptive to prescriptive analytics. You will work with enterprise data to support CX improvement, revenue generation, and cost optimization, leveraging big data, ML, and AI techniques.

You will collaborate with business stakeholders, build end-to-end pipelines, and help operationalize analytics models for real-time insights.

Qualifications

• Experience with Python-based data science workflows and SQL.
• Strong skills in PySpark/SparkR and Big Data processing.
• Proficiency in data visualization and storytelling with code or BI tools.
• Solid understanding of statistical and ML/DL methods for analytics.
• Experience deploying analytics models to production and operational data.
• Ability to build end-to-end data pipelines integrated with models.
• Familiarity with LLMs and AI agents applications.
• Working knowledge of data operations, quality, governance, and data engineering.
• Basic project management skills and cross-functional collaboration.

Responsibilities

• Work with business partners to gather requirements and define analytics use cases.
• Initiate analytics models and data solutions to answer business questions.
• Develop end-to-end big data pipelines for feature engineering and model training.
• Apply statistical, ML and deep learning methods to improve CX, engagement, and efficiency.
• Maintain inventory of past insights, models, and techniques.
• Provide SME input on big data processing and data science during stakeholder discussions.
• Build prototypes and proofs of concept and present outputs to stakeholders.
• Collaborate with Data Analysts for visualization design and data models.

Skills

Python

PySpark

SparkR/R

SQL

Data visualization

R

PowerBI

ML/DL techniques

Data engineering basics

LLM applications

Data ops/governance

Project management

Tools

PowerBI

Job description

The Business Intelligence and Data Science Associate gather requirements, develops, implements, and operationalizes advanced data models for descriptive, diagnostic, predictive and prescriptive analytics using enterprise and operational data to support customer experience and engagement transformation, operational efficiency, revenue generation and protection, cost avoidance and other business metrics. This role has broad and deep knowledge in machine learning, big data processing, and machine learning operations

Responsibilities:

• Work and collaborate with business partners in the requirements gathering and analysis to accurately define required inferences, analytics, and application of data science.

• Initiates analytics models and data solutions to answer business questions and promote data-driven decisions.

• Initiates end-to-end big data pipeline for feature engineering, analytics model training, testing, recalibration, and operationalization.

• Initiates analytical modelling using statistical methods, unsupervised and supervised machine learning algorithms, graphs, and deep learning methods to support customer experience and engagement transformation, operational efficiency, cost optimization, and new revenue creation.

• Maintains an accurate inventory of past insights solutions, processes, models, and techniques.

• Provide subject matter expertise in big data, big data processing, data analytics and data science during consultation discussions with business stakeholders

• Build and construct prototypes and proof of concepts for insights exploration and presents outputs to stakeholders

• Partner with Data Analysts for the design of visualizations and required data models to answer business questions

Required Skills:

• Expertise in Python, PySpark/Spark, SparkR/R scripting, and SQL

• Expertise in data visualization using R and Python or PowerBI

• Expertise in data exploration and, analysis and data storytelling

• Expertise in statistical, machine learning and deep learning techniques for data analytics.

• Expertise in the full data analytics lifecycle including analytics models' operationalization.

• Expertise in building end-to-end big data pipelines with integration to operationalized data models.

• Experience in applications of Large Language Models and AI Agent

• Working knowledge in data operations, quality, governance, and data engineering

• Working knowledge in project management