Data Scientist

Summary

We are looking for a Data Scientist to develop predictive models and data-driven solutions that support business decision-making and customer engagement. The role will focus on developing a lapse propensity model to identify customers at risk of lapsing within the next 90 days, generate customer risk scores, and support personalized retention campaigns to improve customer targeting.

Key responsibilities:

• Collect, extract, clean, and prepare data from various sources for analytical modeling
• Develop and implement statistical models, algorithms, and predictive analytics solutions based on business requirements
• Develop a lapse propensity model to identify customers at risk of lapsing within the next 90 days
• Complete customer scoring to identify and prioritize customers at risk of lapsing
• Support the integration of model outputs into campaigns to enable more personalized customer retention initiatives
• Apply statistical methods, data mining, and machine learning techniques to identify patterns, trends, and business opportunities
• Monitor, test, and evaluate model performance, data accuracy, and overall model quality
• Assess model effectiveness and support measurable improvement in customer targeting
• Collaborate with business and marketing teams to implement analytical models and data-driven solutions
• Communicate findings, insights, and recommendations to relevant stakeholders

Qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Computer Science, or a related field
• At least 3 years of experience in data science, data analytics, or a related data-focused role
• Proficiency in Python and SQL
• Strong knowledge of statistical methods, predictive analytics, and machine learning
• Experience developing, testing, and evaluating predictive models and algorithms
• Experience handling, processing, and analyzing large datasets
• Familiarity with data visualization tools such as Tableau or Power BI
• Strong analytical, problem-solving, and logical reasoning skills
• Ability to communicate complex analytical findings and recommendations clearly
• Good collaboration skills and adaptability in a fast-paced environment