A growth-oriented financial services company is seeking a technically skilled and solutions-oriented Data Scientist- Pricing to join its Analytics team. This hybrid role requires a unique blend of coding expertise, analytical rigor, and collaboration with Sales teams to optimize strategies and drive revenue via pricing. The ideal candidate will excel at translating complex business needs into scalable technical solutions, working closely with Sales to refine product offerings and enhance customer engagement through data-driven insights.
Location: New York, NY (3 days/week)
Salary: Up to 150k base + bonus
Visa Sponsorship NOT AVAILABLE
Responsibilities:
- Enhance and maintain proprietary algorithms using Python to support sales insights and strategy optimization
- Translate financial models and business logic into well-structured, maintainable code that aligns with sales objectives
- Manage code deployment processes with version control, ensuring smooth and reliable releases that support sales initiatives
- Work closely with Sales teams to gather feedback, refine technical solutions, and improve product-market fit
- Analyze market trends and sales data to identify opportunities for revenue growth and improved customer engagement
Requirements:
- Bachelor's degree in a quantitative field (eg, Computer Science, Data Science, Economics, Mathematics, Statistics, Physics).
- Experience in a client-facing technical role (Solutions Consultant) or as a Python developer supporting sales/marketing functions.
- Proficiency in writing production-quality Python code with a focus on supporting business decisions and customer interactions.
- Experience in data analysis using SQL, Python, and Excel, with applications to sales optimization and customer engagement
Preferred (Not a MUST):
- Industry experience in financial services, risk management, or sales/marketing analytics
- Master's in a quantitative field.
- Knowledge of statistical methodologies for sales forecasting, pricing and optimization.
- Experience in data engineering or developing machine learning models for sales analytics