Lead Data Scientist
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Role details
Tech stack
Job description
This is a highly visible leadership role where you’ll partner directly with executives and cross-functional stakeholders to influence key business decisions, improve customer outcomes, and drive measurable financial impact.
You’ll own projects from concept through implementation, applying machine learning, statistical modeling, and business insight to deliver solutions that make a real difference.
What You’ll Do
- Lead analytical initiatives from problem definition through implementation and measurement
- Develop predictive models to support business strategy, financial forecasting, and risk assessment initiatives
- Leverage machine learning techniques such as gradient boosting, random forests, clustering, and segmentation to generate actionable insights
- Identify trends, quantify opportunities, and uncover root causes within large and complex datasets
- Collaborate with senior stakeholders to translate business challenges into analytical solutions
- Present findings and recommendations to leadership through compelling data storytelling and executive presentations
- Guide and mentor less experienced team members on project execution and analytical methodologies
- Build scalable processes and analytical frameworks that improve business performance over time, * High-visibility role with regular interaction with executive leadership
- Opportunity to drive business outcomes through production-ready analytics and machine learning
- Strong autonomy and ownership over projects and strategy
- Work on initiatives with measurable multi-million-dollar business impact
- Mentor and influence without direct people-management responsibilities
- Collaborative, supportive culture that values innovation, curiosity, and continuous improvement
- Opportunity to see your models implemented and your work recognized across the organization
If you’re a data science leader who enjoys solving complex business problems, influencing executive decisions, and building predictive models that drive real-world results, we’d love to connect.
Requirements
- 8+ years of experience in data science, quantitative analytics, predictive modeling, or risk analytics
- Experience applying statistical and machine learning techniques to real-world business problems
- Advanced Python and SQL skills with experience working across large, complex datasets
- Strong understanding of predictive modeling, segmentation, experimentation, and statistical analysis
- Proven track record of influencing business decisions through data-driven recommendations
- Excellent communication skills with the ability to explain complex concepts to executive audiences
- Experience leading initiatives independently with minimal direction
- Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Economics, Engineering, or a related discipline
Nice to Have
- Master’s degree in a quantitative discipline
- Experience within financial services, consumer lending, real estate, healthcare, or other regulated industries
- Background in risk management, portfolio analytics, or credit-related modeling
- Exposure to model validation, governance, audit, or regulatory review processes
- Knowledge of cloud-based data environments including AWS and Snowflake
- Experience utilizing bureau data, scorecards, or advanced forecasting methodologies
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Prepare application
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