Senior Machine Learning Engineer

RCBC; Taguig; On-site; PHP 900,000 - 1,300,000; Full time

Job summary

RCBC is seeking a Data Scientist to build, train, validate, and deploy predictive and prescriptive models for better targeting and decision making across the bank and its third-party partners.

The role focuses on operationalizing ML models, standardizing workflows, monitoring production models, and guiding modeling initiatives within the Data Science & Analytics group to align with RCBC's vision and strategy.

Qualifications

• Degree in Mathematics, Statistics, Computer Science, Engineering, Physics or related field.
• 4+ years of experience in Data Science, Software Engineering, or DevOps.
• Hands-on experience in ML and DL, preferably in banking/finance.
• Developed and deployed modeling projects using ML/DL.
• Integrity, urgency, and analytical mindset.
• Proficiency in ML/DL algorithms, R, Python, Spark, SQL and visualization tools.
• Knowledge in Databricks or other cloud computing tools.

Responsibilities

• Develop, train, test and deploy predictive & prescriptive models using ML/DL algorithms.
• Standardize model development and deployment workflow for robust models.
• Operationalize, monitor, and manage ML models in production.
• Act as SME and provide guidance in modeling initiatives.
• Identify opportunities to apply models to improve customer experience and revenue.
• Proactively source and transform data to improve model accuracy.
• Maintain and update the Model Ops Playbook documenting processes and standards.
• Provide transparency in modeling processes and align with policy guidelines.
• Collaborate with partners on modeling initiatives across groups.
• Ensure deployment of the optimal model after thorough validation.
• Provide modeling guidance and training to peers in the Data Science & Analytics group.
• Validate models built within and outside the organization.

Skills

Machine Learning

Deep Learning

Python

R

SQL

Spark

Visualization tools

Education

Bachelor’s in Math/Stats/CS/Eng

Tools

Databricks

Cloud computing tools

Job description

Job Description

Job Summary

Responsible for building, training, validating and deploying predictive & prescriptive models leveraging machine learning & deep learning algorithms for better targeting and decision making.

This role shall ensure that all models to be deployed, be it in the Bank or with its third-party affiliates and/or partners, are aligned with the Bank's vision and strategies.

How will you contribute?

• Supports Modeling initiatives, ensuring effective delivery of Machine Learning models using global Data Science best practices, technology, tools and methodologies.

The Data Scientist's work scope and capabilities shall cover the following:

• Develop, train, test and deploy predictive & prescriptive models leveraging machine learning and deep learning algorithms.
• Standardize model development and deployment workflow lifecycle to provide robust and credible models.
• Operationalize, monitor and manage Machine Learning models in production.
• Act as a Subject Matter Expert to provide guidance in modeling initiatives across the Data Science & Analytics Group.
• Identify opportunities across the bank and its third-party affiliates where models can be applied to improve customer experience, increase revenue and improve process efficiency.
• Proactively source and transform data to improve model accuracy.
• Maintain and update, as necessary, the Model Ops Playbook which documents processes, standards established in Model Operations, deployment & monitoring.
• Provides transparency in the modeling process and algorithm to ensure that the models are aligned with the Bank's vision, strategy and policy guidelines.
• Collaborates modeling initiatives with partners.
• Ensures deployment of the optimal model, which has gone through rigorous validation against comprehensive algorithms.
• Provides modeling guidance and training to peers within the Data Science & Analytics group.
• Validates models built within and outside the organization.

What will make you successful?

• Degree in Mathematics, Statistics, Computer Science, Engineering, Physics or related field.
• 4+ years of total experience in Data Science, Software Engineering, or DevOps.
• Hands on experience in machine learning and deep learning algorithms preferably in banking, finance, insurance or other related field.
• Developed and deployed modeling projects using machine learning and/or deep learning algorithms.
• Demonstrates professional integrity; with a high sense of urgency, highly analytical.
• Proficiency in machine learning and deep learning algorithms, R, Python, Spark, SQL and visualization tools
• Knowledge in Databricks or other cloud computing tools