Senior Machine Learning Engineer

4 weeks ago

Santa Ana Metro Manila, 00, Philippines Rizal Commercial Banking Corporation (RCBC) Full-time
Function Analytics 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?
- 1. 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:
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- Develop, train, test and deploy predictive & prescriptive models leveraging machine learning and deep learning algorithms.
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- Standardize model development and deployment workflow lifecycle to provide robust and credible models.
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- Operationalize, monitor and manage Machine Learning models in production.
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- Act as a Subject Matter Expert to provide guidance in modeling initiatives across the Data Science & Analytics Group.
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- 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.
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- Proactively source and transform data to improve model accuracy.
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- Maintain and update, as necessary, the Model Ops Playbook which documents processes, standards established in Model Operations, deployment & monitoring.
- 2. Provides transparency in the modeling process and algorithm to ensure that the models are aligned with the Bank’s vision, strategy and policy guidelines.
- 3. Collaborates modeling initiatives with partners.
- 4. Ensures deployment of the optimal model, which has gone through rigorous validation against comprehensive algorithms.
- 5. Provides modeling guidance and training to peers within the Data Science & Analytics group.
- 6. 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
- #LI-NC1