Data Scientist

About the Role: Data Scientist at BPI

Develop analytical models and deliver data-driven solutions using statistical analysis, machine learning, and advanced analytics techniques. Apply data science methodologies to solve complex business problems and generate actionable insights that drive strategic outcomes.

Responsibilities

• Analytical Model Development
  • Develops and implements analytical models using statistical analysis, machine learning, and advanced analytics.
  • Builds and deploys models using AWS cloud services including SageMaker, S3, and related tools.
  • Conducts quantitative analysis including forecasting, optimization, segmentation, and predictive modeling.
  • Performs exploratory data analysis and apply data mining techniques to generate actionable insights.
• Business Collaboration & Delivery
  • Collaborates with stakeholders to understand requirements and translate them into technical specifications.
  • Supports end-to-end project delivery from requirements gathering through model deployment and monitoring.
  • Creates data visualizations, analytical reports, and presentations for stakeholder communication.
• Technical Operations & Quality Assurance
  • Supports data acquisition, processing, and quality assurance activities using AWS services.
  • Assists in model deployment, monitoring, and performance assessment in cloud environments.
  • Conducts validation and testing of analytical models to ensure accuracy and reliability.
  • Maintains documentation of processes, methodologies, and technical specifications.

Qualifications

• Must have a bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or related field.
• Must have 2-4 years experience in data analysis, statistical modeling, or related analytical roles.
• Must have proficiency in programming languages (Python, R, SQL).
• Must have experience with data visualization tools and statistical analysis software.
• Must have understanding of machine learning concepts and data science methodologies.
• Must have strong communication and collaboration skills.
• Must have skills in Python, R, SQL, and data visualization tools.
• Must have skills in statistical analysis and machine learning techniques.
• Must have skills in data processing and database management systems.
• Must have skills in version control systems and collaborative development tools.
• Preferably has proficiency in AWS cloud services and tools (SageMaker, S3, EC2, Lambda).
• Preferably has experience in banking or financial services industry.
• Preferably has advanced degree in relevant field.
• Preferably has certification in data science or analytics.
• Preferably has skills in operations research and optimization methodologies.
• Preferably has skills in geospatial analysis and time series forecasting.
• Preferably has skills in business intelligence and stakeholder management.
• Preferably has skills in data engineering and model deployment technologies.
• Preferably has skills in model monitoring, validation, and governance frameworks.

Work Set-up

Hybrid

Key skills/competency

• Data Science
• Machine Learning
• Statistical Analysis
• AWS Cloud Services
• Python, R, SQL
• Data Visualization
• Predictive Modeling
• Data Mining
• Model Deployment
• Financial Analytics