Data Scientist

Pramerica Life Insurance; Gurugram District, Delhi; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Pramerica Life Insurance is seeking a data science professional to build machine learning models for fraud, underwriting, early claims, and propensity analyses, and to tailor content for online customers based on segmentation.

You will analyze online user behavior, funnel metrics, and multi-channel attribution, formulate marketing hypotheses, and present actionable insights to stakeholders while shaping data collection and reporting processes.

Qualifications

• 4-6 years of experience in Insurance/Banking/Lending/Credit Bureau or Financial sector
• Hands-on experience with Python, Pandas, Numpy, Seaborn, data modeling, feature engineering and developing ML models
• Hands-on experience with Excel, SQL, PowerBI
• Knowledge in creating reporting datasets, data refresh strategy, and role-based data security on reporting tools
• Knowledge in storytelling and presenting actionable insights to stakeholders

Responsibilities

• Checking for trends and identifying anomalies
• Create ML models for Fraud, Underwriting, Early Claims, Propensity to Pay, Propensity to Surrender
• Create ML models to customize content and product offerings for online customers based on segmentation
• Analyzing online user behavior, conversion data, customer journeys, funnel analysis and multi-channel attribution
• Formulate marketing hypotheses and test using statistical techniques
• Use models to predict and allocate prospective leads
• Collecting and interpreting data
• Reporting results, creating funnel and insights back to stakeholders
• Working with teams to establish business needs
• Defining new data collection and analysis processes

Skills

Python

Pandas

Numpy

Seaborn

Data modeling

Feature engineering

ML models

Excel

SQL

PowerBI

Tools

Excel

SQL

PowerBI

Job description

Role & responsibilities

Checking for trends and identifying anomalies

Create Machine Learning model for Fraud, Underwriting, Early Claims, Propensity to Pay, Propensity to Surrender

Create Machine Learning model to customize content and product offerings for online customer based on their customer segmentations

Analyzing online user behavior, conversion data, customer journeys, funnel analysis and multi-channel attribution

Formulate marketing hypothesis and test the same using statistical techniques

Use models to predict and determine how prospective leads should be allocated

Collecting and interpreting data

Reporting the results, creating funnel and report insights back to the relevant stakeholders

Working alongside teams within the business or the management team to establish business needs

Defining new data collection and analysis processes

Preferred candidate profile

Should have 4-6 years of experience in Insurance/Banking/Lending/Credit Bureau or Financial sector

Extensive hands-on experience in working with Python, Pandas, Numpy, Seaborn, data modeling, feature engineering and developing ML models

Extensive hands-on experience in working with Excel, SQL, PowerBI

Should have good knowledge and working experience in creating reporting datasets, creating data refresh strategy and implementing role based data security on reporting tools

Should have good knowledge and working experience in story-telling and presenting actionable insights to stake holders