Data Scientist

Nexus Recruitment Group; Taguig; On-site; PHP 900,000 - 1,500,000; Full time

Job summary

Nexus Recruitment Group is seeking a highly analytical Data Scientist to develop data models, perform advanced analytics, and generate insights for strategic decision-making in a global financial services or insurance environment. You will collaborate with underwriting, actuarial, finance, and operations teams to turn complex data into actionable intelligence.

The ideal candidate brings 3+ years in data science or analytics, strong Python/R skills, SQL, and experience with ML libraries and data

Qualifications

• Bachelor's or Master's degree in Data Science, Statistics, CS, Mathematics, or related quantitative field.
• 3+ years in data science/analytics, ideally in insurance/finance/risk-heavy industries.
• Proficiency in Python or R, SQL, and data visualization tools (Power BI/Tableau/matplotlib).
• Experience with ML libraries (scikit-learn, XGBoost, TensorFlow) and statistical modeling techniques.

Responsibilities

• Design and implement predictive models and ML algorithms for business problems.
• Analyze large datasets to identify patterns across risk, claims, and financial operations.
• Develop dashboards and automated reports for technical and non-technical users.
• Collaborate with business units to translate needs into data solutions.
• Ensure data quality and integrity across the data pipeline.
• Present findings to senior stakeholders with clear insights.
• Support deployment of models into business workflows.

Skills

Python

SQL

Data Visualization

Cloud platforms

Machine learning

Education

Bachelor's/Master's in Data Science

Tools

Power BI

Tableau

Git

scikit-learn

Job description

We are looking for a highly analytical and business-driven Data Scientist to develop data models, perform advanced analytics, and generate insights that drive strategic decision-making in a global financial services or insurance environment. This role will work closely with cross-functional teams in underwriting, actuarial, finance, and operations to turn complex data into actionable intelligence.

The ideal candidate is experienced in predictive modeling, statistical analysis, and data engineering, with a strong understanding of how data science supports risk management, pricing, claims, and customer analytics.

Key Responsibilities:

• Design and implement predictive models, machine learning algorithms, and data-driven tools to solve business problems.
• Analyze large, complex datasets to identify patterns, trends, and opportunities across risk, claims, and financial operations.
• Develop dashboards, visualizations, and automated reports for technical and non-technical users.
• Collaborate with business units to understand needs and translate them into data solutions.
• Ensure data quality, consistency, and integrity throughout the data pipeline.
• Present findings and recommendations to senior stakeholders using clear, actionable insights.
• Support the deployment and integration of models into business workflows and systems.
• Stay current with emerging technologies and techniques in data science and advanced analytics.

Qualifications:

• Bachelors or Masters degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• 3+ years of experience in a data science or analytics role, ideally in insurance, finance, or risk-heavy industries.
• Strong proficiency in Python or R, SQL, and data visualization tools (e.g., Power BI, Tableau, or matplotlib).
• Experience with machine learning libraries (e.g., scikit-learn, XGBoost, TensorFlow) and statistical modeling techniques.
• Familiarity with cloud platforms (e.g., AWS, Azure, or GCP) and version control tools (e.g., Git).
• Excellent problem-solving, data storytelling, and communication skills.
• Ability to manage multiple projects and deliver results in a fast-paced environment.