Data Scientist (Varying Levels)
Windfall
Responsibilities:
- Build and Deploy Custom Models: You will own the end-to-end lifecycle of customer-facing machine learning models—from initial data exploration and feature engineering to model training, validation, deployment, and ongoing evaluations.
- 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.
- Drive Product Innovation: You will act as a key technical partner to our Product and Customer Success teams, providing insights that shape our modeling strategy and helping to translate complex customer needs into scalable data science solutions.
- Think Outside the Box: You will tackle ambiguous problems and develop creative modeling strategies to address unique customer challenges across a variety of industries.
- Communicate with Impact: You will be responsible for clearly communicating model performance, methodology, and business impact to both technical and non-technical stakeholders.
Requirements:
- 5+ years of professional industry experience in a data science or machine learning role.
- Proven, hands-on experience building and deploying production-level predictive models (e.g., classification, regression, clustering).
- Expert proficiency in Python and its core data science libraries (e.g., pandas, scikit-learn, NumPy, XGBoost).
- Advanced proficiency in SQL for complex data manipulation, aggregation, and analysis.
- A strong product-oriented mindset, with a demonstrated ability to connect data science work to tangible business value and customer success.
- Experience with the full machine learning lifecycle, including scoping, feature engineering, validation, deployment, and monitoring.
- The ability to communicate technical ideas to a non-technical audience.
Preferred Qualifications:
- Experience with containerization technologies like Docker and an understanding of how they are used to deploy models.
- Experience building and orchestrating simple data pipelines using tools like 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.
180000 - 230000 USD a year