AI and Data Science Trainee

Orangeandbronze; Muntinlupa; On-site; PHP 279,000 - 390,600; Full time

Job summary

Orangeandbronze is seeking an AI and Data Science Trainee responsible for designing data modeling processes, creating algorithms, and developing predictive models.

The role involves consulting with stakeholders, aligning data with organizational goals, and analyzing datasets. The position is hybrid and full-time, based in Makati.

Qualifications

• Knowledge of Python or R for data manipulation.
• Basic to intermediate SQL skills (joins, aggregations, subqueries).
• Familiarity with building and evaluating machine learning models.

Responsibilities

• Design data modeling processes and establish structure.
• Create algorithms to solve business problems.
• Develop predictive models to forecast trends.

Skills

Python or R

Applied Statistics

SQL

Machine learning lifecycle

A/B testing

Looker Studio, Tableau, Power BI

Education

Bachelors Degree in Mathematics, Statistics, Computer Science, Economics, or Industrial Engineering

Job description

The AI and Data Science Trainee is responsible for designing data modeling processes, creating algorithms, and developing predictive models to extract essential business data.

S/he works closely with both internal and external business stakeholders. This involves understanding the organization’s goals and identifying ways to leverage data to achieve them.

Work Setup: Hybrid

Work Location: Makati

Duties and Responsibilities

• Designing Data Modeling Processes: Establish how data should be structured and connected to support analytical needs.
• Algorithm Creation: Writing custom code and logic to solve specific business problems rather than just using “out-of-the-box” tools.
• Predictive Modeling: Develop machine learning models to forecast future trends, customer behaviors, or business outcomes.
• Data Extraction: Identify and pull essential data points from larger, noisier datasets.
• Bridging Data and Goals: Translating raw numbers into actionable insights that directly align with what the organization is trying to achieve.
• Internal & External Consultation: Acting as a bridge between technical teams and non-technical partners (like clients or other departments).
• Goal Alignment: Actively listen to business leaders to ensure the data science roadmap actually solves their most pressing problems.

Technical Must-haves:

• Knowledge of Python or R for data manipulation and algorithm development.
• Knowledge of or exposure in Applied Statistics.
• Basic to intermediate SQL skills (joins, aggregations, and subqueries).
• Familiarity with the machine learning lifecycle, including building and evaluating models such as Regression or Random Forest.
• Experience with A/B testing, hypothesis testing, and validating model performance using rigorous statistical metrics is a plus.
• Experience with tools like Looker Studio, Tableau, Power BI, or similar to create intuitive dashboards is a plus.
• Experience through internships, academic coursework, or personal portfolios (e.g., GitHub/Kaggle) is highly valued.

Required Skills & Qualifications

• Bachelors Degree in a highly quantitative field: Mathematics, Statistics, Computer Science, Economics, Industrial Engineering, or a related discipline.
• Open to Fresh Graduates and Career Shifters.
• Open to those without experience, but willing to be trained.
• Able to approach data without bias, questioning assumptions and verifying the “why” behind data anomalies before drawing conclusions.
• Proficient in extracting trends from noisy or unstructured datasets to forecast future behaviors.
• Capable and adaptable to pivoting strategies or switching algorithmic approaches when initial hypotheses are disproven by the data.
• Adept at converting vague stakeholder pain points into precise technical requirements and actionable “business-speak.”
• Works effectively within agile environments, contributing to code reviews, and participating in whiteboarding sessions with engineers.
• Able to manage differing priorities between departments (e.g., balancing the Engineering need for stability with the Business need for rapid deployment).
• Ability to translate complex statistical findings into clear, actionable “business-speak” for executive stakeholders.
• Proven ability to manage expectations and provide data-driven recommendations to both internal teams and external stakeholders.

Seniority Level

Junior and Mid-Level

Employment Type

Full-time

Job Function

Information Technology, Project Management, Consulting, and Engineering

IT Services, IT Consulting, and Software Development