Data Scientist at EastWest Bank

Makati, Metro Manila, Philippines -

Full Time

Start Date

Immediate

Expiry Date

27 Sep, 26

Salary

0.0

Posted On

29 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, R, SQL, Machine Learning, Statistical Modeling, AI Modeling, Data Wrangling, Feature Engineering, Exploratory Data Analysis, MLOps, Model Deployment, Model Monitoring, Communication, Collaboration, Critical Thinking, Problem Solving

Industry

Banking

Description

About the Job Location: Taguig Corporate Title: Junior Officer to Senior Manager Work Arrangement: Hybrid Our Enterprise Data Office team is looking for experienced professionals to join us in Taguig with the role of Data Scientist. In this role you will design, develop, and deploy machine learning and statistical models to solve complex business challenges, contributing to data products that drive revenue, strengthen risk management, and improve operational efficiency. You will collaborate with product managers, engineers, and business stakeholders to deliver actionable insights and real-time analytics, with responsibilities tailored to your level from junior support to executive leadership. Your dream. Our focus. East West Banking Corporation (EastWest) is one of the largest universal banks in the Philippines, and is committed to continuously invest in people and in process, product, and service enhancements, and embrace new ideas to enhance the EastWest experience. We empower our employees to drive their careers and are committed to provide the runway for them to grow. We value teamwork and individual initiative. Join us and be part of a highly engaged team, and a workplace that promotes development and goal attainment. Whether you're just starting out, or already a seasoned professional, EastWest can help you unleash your potential, and bridge the gap between dream to success. What the role will entail Design and develop machine learning, statistical, and AI models for applications such as credit, fraud, customer behavior, and operations. Conduct data wrangling, feature engineering, and exploratory analysis to prepare datasets for modeling. Validate models and collaborate with engineering teams to deploy them into production environments. Partner with business stakeholders to translate problems into analytical requirements and present results in clear business terms. Participate in continuous learning, research, and knowledge-sharing within Communities of Practice, contributing to mentoring and capability building. Support enterprise data product delivery, compliance with AI risk management standards, and other strategic initiatives as assigned. What we're looking for Bachelor's Degree in either Computer Science, Statistics, Mathematics, Engineering, Economics, or related quantitative field; Master's degree preferred Certifications such as TensorFlow Developer, Microsoft Data Scientist, or equivalent are advantageous but not required. Relevant experience ranges from 0–2 years for junior roles up to 8+ years for lead roles, with emphasis on data science, model deployment, and financial services expertise. Strong proficiency in Python, R, SQL, and familiarity with machine learning frameworks; knowledge of MLOps, model monitoring, and banking domain use cases is a plus. Demonstrated competencies in communication, collaboration, critical thinking, problem-solving, and leadership, with increasing levels of expertise expected across junior to lead roles. What you can expect from joining our team Career development and training opportunities Competitive salary package and benefits Performance-based incentives and recognition programs to reward high-performing individuals Opportunity to work with industry experts and be mentored by them Defined career progression paths to guide you in your professional growth

Responsibilities

Design, develop, and deploy machine learning and statistical models to solve complex business challenges in credit, fraud, and customer behavior. Collaborate with stakeholders and engineering teams to deliver actionable insights and real-time analytics into production environments.