Senior Data Scientist

ABOUT THE ROLE:

Splash Financial is seeking a Data Scientist with strong programming skills in Python and experience creating complex algorithm models.

The ideal candidate is tenacious, proactive, and takes ownership of their deliverables. They constantly seek improvement, set high standards for data quality and analysis, and troubleshoot issues methodically using various data science tools. They write thoughtful designs and documentation, hold themselves and others accountable, and provide and receive feedback with compassionate candor. Collaboration and a constructive spirit are essential, as we value directness and candor but do not tolerate unconstructive negativity. We are solution builders, and our culture is critical to our success.

Join our team that values growth, flexibility, and work/life balance! Mentor others and be mentored, ideate new projects, take ownership, and execute.

WHAT YOU'LL DO AT SPLASH:

• Analyze and interpret complex datasets to generate clear, actionable insights that inform business and product decisions.
• Design, build, and deploy machine learning models that enhance underwriting, risk management, customer experience, and other core fintech functions.
• Write clean, efficient Python code for data analysis and model development.
• Collaborate with cross-functional teams to understand their data needs.
• Provide constructive feedback on data analyses and model implementations.
• Work within an OKR-driven organization with a clear mission.
• Participate actively in our highly collaborative, fully remote culture.

WHAT YOU'LL BRING TO SPLASH:

• At least 3-5+ years in data science, machine learning, or a closely related field, ideally in a fast-paced environment.
• Advanced degree (MS or PhD) in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Economics, Engineering). PhD-level research or industry experience, especially with a hypothesis-driven problem-solving approach, is highly valued.
• Proficiency in Python for data analysis, modeling, and production-level code.
• Experience with classical machine learning and a solid understanding of statistical modeling, feature engineering, and model evaluation techniques.
• High candor, providing and accepting constructive feedback graciously.
• Understanding that there can be multiple correct solutions, with a willingness to disagree and commit.
• Experience in unsecured lending and installment loan industries is a big plus.

COMPENSATION:

The base salary range for this role is $150,000 to $200,000 annually, based on market data and internal compensation practices. This role may also be eligible for a bonus component tied to individual and company performance. Final compensation will be determined by factors such as location, experience, and skill level.