Data Scientist

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