Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global technology platform is dedicated to helping individuals and nonprofits raise funds for personal causes and charitable initiatives. Since its launch, the platform has empowered millions of people worldwide by providing a trusted and accessible fundraising experience while leveraging technology to drive positive social impact.
Key Responsibilities
- Own end-to-end donation pricing and amount optimization, including analytical strategy, modeling frameworks, and success metrics.
- Develop pricing recommendations that balance donation conversion, donation value, and long-term donor trust.
- Apply economic theory, behavioral science, and machine learning to model donor decision-making and estimate price elasticity.
- Analyze sparse and non-transactional behavioral signals, including navigation patterns, hesitation, context, device usage, and timing, to understand donor intent.
- Design adaptive pricing models using experimentation signals, feedback loops, and reinforcement learning concepts such as contextual bandits and sequential decision-making.
- Partner with Product and Engineering teams to build robust experimentation frameworks and causal measurement systems.
- Integrate external datasets, including macroeconomic trends, seasonal patterns, and regional signals, into predictive behavioral models.
- Translate complex economic and behavioral analyses into deployable machine learning models, actionable product recommendations, and measurable business impact.
- Communicate insights effectively to senior leadership through clear storytelling and data-driven recommendations.
- Establish best practices for model development, validation, monitoring, and continuous improvement while mentoring fellow data scientists.
Required Qualifications
- Ph.D. in Economics, Applied Economics, or a closely related quantitative field, or 8+ years of industry experience in data science, applied economics, pricing, marketplace optimization, or monetization within a technology-driven organization.
- Proven experience building and scaling pricing, optimization, or decision-making systems.
- Strong background in econometrics, causal inference, behavioral modeling, and applied economic reasoning.
- Demonstrated ability to solve ambiguous, high-impact business problems using data-driven approaches.
- Deep understanding of price elasticity, choice modeling, and decision science.
- Experience modeling noisy, sparse, or non-transactional behavioral data.
- Hands-on experience designing, executing, and interpreting experiments and causal analyses.
- Familiarity with reinforcement learning, contextual bandits, or adaptive optimization methodologies.
Technical Skills
- Advanced proficiency in Python, including libraries such as pandas, NumPy, scikit-learn, PyMC/Stan, or equivalent frameworks.
- Strong SQL skills for complex data analysis and modeling workflows.
- Experience leveraging modern AI tools, LLM-based assistants, autonomous coding agents, synthetic data generation, and AI-assisted feature engineering.
- Experience designing or implementing AI-powered solutions for decision-making, rapid experimentation, simulation, or model orchestration beyond prompt engineering.
Leadership & Collaboration
- Excellent communication and storytelling skills for presenting complex analytical findings to technical and executive stakeholders.
- Ability to influence product strategy and executive decision-making through data-driven insights.
- Demonstrated success leading through influence and elevating technical standards across data science teams.
Preferred Qualifications
- Experience with consumer pricing, digital marketplaces, payments, or donation platforms.
- Experience partnering with engineering teams to productionize AI and machine learning models, including monitoring, evaluation, and continuous iteration.
- Familiarity with modern data platforms such as Snowflake and Databricks.
- Experience with experimentation infrastructure, model versioning, and validation frameworks.
- Strong data visualization, documentation, and executive presentation skills.
Disclaimer
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- No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
- No Client Relationship: This company is not a client of SpringCube unless stated.
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