Data Scientist-Mid

Company Description

Arch Global Services (Philippines) Inc. is a proud member of the Arch Capital Group LLC (www.archgroup.com), a globally recognized leader in insurance, reinsurance, and mortgage insurance solutions.

Established as the Group’s Global Service Operations (GSO) hub in the Philippines, Arch Global Services delivers critical support to Arch Capital’s worldwide network. We provide high-quality, high-impact business services across key areas such as Finance, IT, Risk, Actuarial, Operations, Project Management, Data & Analytics, and Shared Services.

At Arch, we believe in empowering our people with meaningful work, continuous learning, and a collaborative culture that values innovation, agility, and integrity. Our dynamic Manila and Cebu-based teams play a vital role in driving operational excellence and digital transformation for the Arch enterprise.

Joining Arch Global Services means being part of a fast-growing, high-performing organization that offers global exposure, professional development, and a strong commitment to work-life balance. If you’re looking to grow your career in a company that values talent, purpose, and potential — we invite you to build your future with us.

Be part of something bigger. Be part of Arch. Where the people is our biggest asset!

Job Description

Strategic Analytics is a growing team at Arch focused on delivering data-driven solutions that improve business performance. We develop intelligent data automation capabilities that combine external data with Intelligent Document Processing (IDP) and AI/ML technologies to extract and structure information from unstructured sources.

In this role, you will support the design and implementation of IDP and AI solutions across claims. This includes preparing data for document processing, transforming outputs into structured datasets, and contributing to automated document extraction and data enrichment workflows.

You will collaborate with business stakeholders, engineers, and data scientists to translate business problems into technical solutions.

• Collaborate with business customers and engineers to translate business problems into technical solutions and deliver automated document extraction and data enrichment solutions.
• Manipulate data using Python and SQL Server; develop ad hoc queries to investigate data anomalies and to summarize data for pattern detection.
• Manually label and validate training datasets.
• Under supervision use AI technologies such as natural language processing to extract business data from unstructured and semi-structured sources (e.g., loss history reports, insurance applications, claim files, application scraping using OCR/ generative AI, etc.).
• Create technical documentation to archive end-to-end processes.
• Implement evaluation frameworks using precision, recall, F1 scores, accuracy, and operational metrics
• Build solutions to monitor and continuously evaluate performance of implemented solutions.
• Collaborate with experienced modelers to build predictive models and analytic solutions; apply machine learning techniques such as decision trees and clustering.

Qualifications

• Experience in manipulating, processing and extracting value from datasets
• Exposure to data science, software development, engineering or equivalent
• Detail-oriented with strong organizational skills
• Strong critical thinking skills to tackle complex data challenges
• Strong communication skills that convey statistical and business impact, proactively surface issues
• Comfortable working in a fast-paced and highly collaborative global team
• Experience in Python, SQL, and Git

Preferred Skills/Experience

• Experience with evaluation frameworks, experimental design
• Experience with OCR, NLP, and/or image analytics
• Experience with cloud technologies and implementing data science/AI solutions.
• Experience configuring & establishing automations utilizing IDP software solutions

The ideal candidate will have experience working in the insurance industry

Additional Information

• Bachelor’s degree in data science, analytics, statistics, actuarial science, mathematics, engineering or similar quantitative fields; or significant experience in data analytics