Senior Data Analyst

Magma General Insurance Limited; Mumbai; On-site; INR 1,500,000 - 2,200,000; Full time

Job summary

Magma General Insurance Limited seeks an Analytics & Data Science professional with 5–7 years of experience to develop data-driven solutions in fraud detection, risk projection, and underwriting analytics.

You will build scalable pipelines in Python/SQL, design ML workflows, and collaborate with stakeholders to deliver dashboards in Power BI/Qlik Sense, shaping data-informed decisions across the business.

Qualifications

• 5–7 years of analytics and data science experience in insurance or financial services.
• Strong Python and SQL proficiency.
• Experience with ML techniques and model lifecycle management.
• Experience with Power BI or Qlik Sense visualization.
• Understanding of ML deployment and MLOps concepts.

Responsibilities

• Develop and deploy ML models for fraud detection, underwriting risk, and customer risk profiling.
• Build scalable data pipelines and feature engineering frameworks using Python and SQL.
• Design end-to-end ML workflows including model training, validation, and deployment.
• Work with business stakeholders to translate business problems into analytical solutions.
• Perform exploratory data analysis (EDA), model monitoring, and performance tuning.
• Create impactful dashboards and reports using Power BI/Qlik Sense for decision-making.
• Collaborate with data engineering and IT teams for production-grade model deployment.

Skills

Python

SQL

Power BI

Qlik Sense

Stakeholder management

Communication

Tools

Azure ML

AWS SageMaker

Vertex AI

Job description

We are seeking highly skilled Analytics & Data Science professionals (5–7 years of experience) with strong domain expertise in Insurance/Financial Services. The role focuses on developing data-driven solutions across Fraud Detection, Risk Prediction, and Underwriting Analytics.

Key Responsibilities

• Develop and deploy machine learning models for fraud detection, underwriting risk, and customer risk profiling.
• Build scalable data pipelines and feature engineering frameworks using Python and SQL.
• Design and implement end-to-end ML workflows including model training, validation, and deployment.
• Work with business stakeholders to translate business problems into analytical solutions.
• Perform exploratory data analysis (EDA), model monitoring, and performance tuning.
• Create impactful dashboards and reports using Power BI/Qlik Sense for decision-making.
• Collaborate with data engineering and IT teams for production-grade model deployment.

Required Skills & Qualifications

• 5–7 years of experience in Analytics & Data Science roles.
• Domain experience in Insurance or Financial Services (Fraud, Risk, Underwriting preferred).
• Strong programming skills in Python and SQL.
• Hands-on experience with machine learning techniques and model lifecycle management.
• Experience with visualization tools such as Power BI/Qlik Sense.
• Understanding of ML deployment and MLOps concepts.

Good to Have

• Experience with cloud ML platforms such as Azure ML, Google Vertex AI or AWS SageMaker.
• Exposure to big data ecosystems and real-time data processing.
• Knowledge of regulatory and compliance considerations in financial services (preferably Insurance)
• Strong analytical and problem-solving skills.
• Ability to work in a fast-paced, business-driven environment.
• Excellent communication and stakeholder management skills.