Pricing and Customer Lifetime Value Analyst - Data Scientist

October 20

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Description

• Your role sits in the pricing and customer lifetime value management team. • Play a critical part in enhancing loan pricing strategies by leveraging advanced analytics and modelling techniques. • Develop valuable commercial knowledge and technical experiences while working with senior commercial stakeholders and experienced data scientists. • Perform regular monitoring of the conversion rate and pricing performance of the portfolio and pricing tests. • Identify opportunities for pricing improvement and optimisation and make data-driven recommendations. • Adjust the pricing logic in Python to implement price changes. • Conduct necessary pricing accuracy checks to ensure implementation is error-free. • Develop and improve the pricing algorithm that automatically optimises for total profit within business hurdles. • Use test-and-learn approach to generate insights that can drive actions and improve the portfolio profitability. • Support the design and implementation of the test. • Develop and implement predictive models for various business needs.

Requirements

• Proficiency in data manipulation, statistical analysis and modelling, using tools such as Python, SQL or similar. • Good statistical knowledge and practical experience in designing and conducting A/B tests. • Experience with machine learning techniques and data mining is preferred. • Strong attention to detail, problem-solving skills and a data-driven mindset. • Proven ability to analyse large datasets, extract meaningful insights, and make data-backed recommendations. • Solid understanding of personal lending products and the pricing dynamic. • Ability to translate technical findings into business insights. • Exceptional communication and presentation skills. • Ability to interact effectively with cross-functional teams and convey complex technical concepts to non-technical stakeholders. • Collaborative and adaptable with a strong sense of ownership and accountability. • Experience in the financial service industry is preferred. • Bachelor's degree in a relevant field such as Data Science, Statistics, Computer Science, Mathematics, or a related discipline. • Advanced degrees (Master's or Ph.D.) are a plus. • Strong written and verbal communication skills in English. • Previous experience in data science, analytics, or modelling roles within the financial industry is a plus.

Benefits

• Family-friendly and flexible working hours and generous home office regulations, • Ergonomic workstations for your days in the office • Short decision-making processes to work independently • Plenty of room for creativity and development, including an annual development budget • Numerous events across all divisions! • Train ticket or parking space subsidies • Company-owned bicycle cellar to safely store your bike • Free sports activities or discounted membership at Fitness First or Urban Sports Club • Subsidies for the company pension scheme • Offers to suit individual lifestyles (corporate benefits program, offers for parents, travel enthusiasts...)