Staff Data Scientist

At Windfall, data science is central to our mission as a people data and AI company. We aim to revolutionize how organizations perceive and utilize people data by providing leading commercial and nonprofit partners with accurate and actionable predictive models.

We are looking for a deeply technical Staff Data Scientist to join our Modeling & AI team. In this role, you will be the go-to expert for our most complex modeling challenges. You will be a hands-on-keyboard architect, designing and building sophisticated, scalable machine learning systems that power our model offerings. You'll spend your time tackling ambiguous problems, pioneering novel modeling techniques, and writing production-grade code that elevates the technical bar for the entire team.

Your work will be directly applied, as you collaborate closely with customers to develop a range of models—from sophisticated marketing and lead scoring models to donation likelihood models that empower top nonprofit organizations worldwide. This position is ideal for an individual who is passionate about deep technical exploration, solving challenging technical problems, and constructing robust, end-to-end ML solutions that deliver immense value to our clients.

• Architect and Own Modeling Solutions: You will lead the design and own the end-to-end lifecycle of our most sophisticated machine learning models, from ideation and strategic planning through to deployment and long-term performance monitoring.
• Synthesize Diverse Datasets: You will become an expert at blending first-party customer data with Windfall's proprietary data assets to engineer novel features and build highly predictive models.
• Build for Scale: You will go beyond individual models to design and build scalable, reusable data pipelines and modeling frameworks that improve the efficiency and capabilities of the entire team.
• Innovate and strategize: Address complex, ambiguous problems and craft creative modeling solutions to meet diverse customer needs across various industries.
• Communicate with Impact: You will be responsible for clearly communicating model performance, methodology, and business impact to both technical and non-technical stakeholders.

• 8+ years of professional industry experience in data science, with a proven track record of leading complex machine learning projects from conception to completion.
• Deep, expert-level knowledge of machine learning theory and its practical application, including extensive experience with classification, regression, and feature engineering.
• Mastery of Python and its data science ecosystem.
• Expert-level SQL skills, with the ability to write optimized queries against large-scale datasets.
• A strategic, product-driven mindset with a history of influencing product roadmaps and tying data science initiatives directly to business outcomes.
• Hands-on experience with the engineering aspects of data science, including proficiency with Docker for containerization and experience building and deploying data pipelines.
• Eligible to work within the United States.

• Experience designing and implementing MLOps best practices for model monitoring, versioning, and automated retraining.
• Familiarity with modern cloud data platforms (e.g., BigQuery) and pipeline orchestration tools (e.g., Airflow).
• Experience working in marketing analytics, ad-tech, fintech, or for a nonprofit organization.
• A Master's degree or Ph.D. in a quantitative field such as Statistics, Computer Science, Economics, or Mathematics.

About Windfall

Windfall is a people intelligence and AI company that gives go-to-market teams actionable insights. By democratizing access to people data, organizations can intelligently prioritize go-to-market resources to drive greater business outcomes. Powered by best-in-class machine learning and artificial intelligence, Windfall activates insights into workflows that engage the right people for each respective organization. More than 1,500 data-driven organizations use Windfall to power their business. For more information, please visit www.windfall.com.

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