Data Scientist

Philippine Batteries Incorporated; Quezon City; On-site; PHP 900,000 - 1,500,000; Full time

Job summary

Philippine Batteries Incorporated is seeking a Data Scientist — Modelling to develop and validate statistical and machine‑learning models that improve predictions, decisions and measurable value across manufacturing and operations.

The role frames problems to business outcomes, establishes baselines, tests forecasting methods, performs feature engineering, builds models for forecasting, quality, pricing and optimization, and documents assumptions and limitations for auditable workflows.

Qualifications

• Bachelor-level or higher in quantitative field; masters preferred.
• 3+ years building and deploying statistical or ML models with production use.
• Manufacturing/quality or demand-forecasting modelling experience is a plus.

Responsibilities

• Frame modelling problems against measurable business outcomes and a decision point.
• Establish the baseline the model must beat and define success/failure criteria.
• Test forecasting algorithms against the baseline to improve accuracy.
• Perform feature engineering, model development, validation, backtesting and explainability.
• Develop forecasting, quality, customer, maintenance, pricing and optimization models as assigned.
• Document assumptions, data needs and failure modes.
• Define acceptance criteria, monitoring, retraining triggers and retirement rules.
• Collaborate with data/AI engineers to deploy models in operational workflows.
• Monitor model performance and drift; act when needed.
• Quantify value earned against the baseline after deployment.
• Report if a model does not beat baseline and recommend retirement.
• Produce model cards, evaluation reports and backtesting records.
• Maintain monitoring plans and drift/retraining schedules.
• Document business impact and reproducible experiments.

Skills

Statistical modelling

Machine learning

Forecasting

Experiment design

Feature engineering

Model deployment

Data visualization

Education

Bachelor's degree in Statistics/Math/CS/Eng/Econ

Master's degree preferred

Tools

Python

SQL

Spark

Databricks

Job description

The Data Scientist — Modelling develops and validates statistical and machine-learning models that improve prediction, diagnosis, optimization and business decisions. The role is accountable not only for model quality but for whether the model changes a decision and produces measurable value.

Responsibilities:

• Frame modelling problems against a measurable business outcome and a specific operational decision point.
• Establish the baseline that the model must beat, and define what success and failure look like before development starts.
• Test new forecasting algorithms and machine-learning approaches against that baseline.
• Perform feature engineering, model development, validation, backtesting, explainability analysis and experiment design.
• Develop forecasting, quality, customer, maintenance, pricing and optimization models depending on assigned domain.
• Document assumptions, limitations, data requirements and failure modes.

Productionization and lifecycle

• Define model acceptance criteria, monitoring requirements, retraining triggers and retirement conditions.
• Work with data and AI engineers to integrate models into actual operational workflows rather than standalone notebooks.
• Monitor deployed model performance and drift, and act when performance degrades.

Value measurement

• Quantify incremental business value against the baseline after deployment.
• Report honestly where a model does not beat the baseline and recommend retirement.
• Production models with documented model cards.
• Evaluation and backtesting reports.
• Monitoring plans, drift reports and retraining schedules.
• Business-impact measurement against baseline.
• Reproducible experiment records and feature documentation.

Accountability and Success Measures

• Statistical validity and reproducibility of models.
• Explainability appropriate to the decision and the audience.
• Decision utility — whether the model changes what people do.
• Measured performance and value after deployment, not at development time.
• Honest reporting of model limitations.

Qualifications

• Bachelor's degree in Statistics, Mathematics, Computer Science, Engineering, Economics or a related quantitative field. Master's degree preferred for senior positions.
• Three or more years developing and deploying statistical or machine-learning models with demonstrated production use. Manufacturing process, quality or demand-forecasting modelling experience preferred for site-assigned positions
• Preferred: Databricks Machine Learning Associate or Professional. Optional: cloud machine-learning certification, specialized forecasting or reliability training.