Lead Data Scientist
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Role details
Tech stack
Job description
A leading organization is seeking a Lead Data Scientist to drive advanced risk and financial modeling initiatives that directly influence business performance. This is a highly visible individual contributor role for a senior-level data scientist who can independently lead complex projects, quantify business impact, and effectively communicate insights to executive stakeholders.
This team is responsible for identifying significant financial opportunities, developing predictive models, and delivering measurable outcomes. Success in this role requires strong technical expertise, business acumen, and the ability to defend models in regulated environments.
Responsibilities
- Lead end-to-end data science projects from problem definition through implementation.
- Develop, validate, and monitor predictive and risk models using large-scale financial and customer datasets.
- Apply advanced statistical and machine learning techniques, including gradient boosting models.
- Translate model outputs into actionable business recommendations and financial impact.
- Present findings, model performance, and recommendations to senior leadership and executive stakeholders.
- Support model governance activities, audits, and validation reviews.
- Mentor and support team members while serving as a technical leader within the organization., * Direct ownership of high-value analytics initiatives.
- Opportunity to see models implemented and tied to measurable business outcomes.
- Significant executive exposure and influence.
- High-impact, collaborative team where individual contributions are highly visible.
- Ability to drive projects that identify and deliver multi-million-dollar business opportunities.
Requirements
- 8+ years of experience in data science, quantitative analytics, or predictive modeling.
- Strong background in finance, credit, or risk modeling within a regulated industry.
- Advanced Python and SQL skills.
- Strong foundation in mathematics, statistics, and predictive modeling.
- Experience building and validating models used for financial or risk-related decision making.
- Experience presenting technical concepts and model results to executive audiences.
- Proven ability to independently own and deliver complex projects.
- Experience supporting external audits and defending analytical models.
Preferred Experience
Experience in one or more of the following areas:
- Credit risk modeling
- Probability of Default (PD) modeling
- Credit loss or loss forecasting models
- Scorecard development
- Payment behavior analytics
- Banking, lending, mortgage, credit card, or credit bureau data
- Financial impact and portfolio analysis
Education
- Bachelor’s degree in Mathematics, Statistics, Economics, Computer Science, Engineering, or another quantitative discipline required.
- Master’s degree in Data Science, Statistics, Mathematics, Economics, Engineering, or a related quantitative field preferred.
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