- Location
- Quezon City, Bridgetowne Zeta, Philippines
- Workplace
- Remote
- Type
- Full-time
- Department
- IT
- Seniority
- Senior
- Closing date
- Today
- Source
- Workday
Description
Sagility combines industry-leading technology and transformation-driven BPM services with decades of healthcare domain expertise to help clients draw closer to their members. The company optimizes the entire member/patient experience through service offerings for clinical, case management, member engagement, provider solutions, payment integrity, claims cost containment, and analytics. Sagility has more than 25,000 employees across 5 countries.
Job title:
Job Description:
Key Responsibilities
• Own end-to-end delivery of regular MIS reporting, dashboards, and ad-hoc analysis
• Drive deep-dive analytics to uncover trends, risks, and opportunities
• Lead AI/ML model development and advanced analytics initiatives
• Define and implement data models and ETL/data pipelines
• Partner with stakeholders across Finance, Sales, HR, Risk, and Operations
• Drive budgeting, forecasting, and PnL analytics support
• Identify automation and process improvement opportunities
• Establish governance, SOPs, and best practices
• Lead and mentor analytics teams
Required Skills
• MIS reporting, dashboarding, and data storytelling
• Statistics and hypothesis testing
• Machine Learning (regression, classification, clustering)
• AI / Deep Learning (good to have)
• Excel (advanced), SQL, Python (pandas, NumPy)
• R / SAS / SPSS (optional)
Tools & Technologies
• Visualization: Power BI, Tableau, Qlik, Looker
• Databases: SQL Server, Oracle, Teradata, Big Query, Snowflake
• ETL: SSIS, Informatica, Azure Data Factory, dbt, Kafka
• Cloud: Azure, AWS, GCP
Expectations
• Strong stakeholder engagement and communication
• Ability to work independently
• Requirements gathering and documentation
• Project management and cross-functional collaboration
• Mentoring and coaching team members
Success Measures
• Timely and accurate delivery of analytics outputs
• Business impact from analytics and AI initiatives
• Adoption of data-driven decision making
• Efficiency gains through automation
• Team growth and stakeholder satisfaction
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