Windfall
Principal Data Scientist - Foundational Models
Windfall, San Francisco, California, United States, 94199
About WindfallAt Windfall, we leverage data-driven insights to help organizations achieve their goals, from non-profits boosting their fundraising efforts to commercial companies improving their marketing ROI. We are looking for a seasoned Principal Data Scientist to play a pivotal role in developing and scaling our foundational predictive models, such as household net worth and investable assets. This is a highly impactful role where you will influence the core of our data product offerings and collaborate with cross-functional teams to maintain the highest standards of model performance.
We’re on a mission to change how organizations perceive and use people data - and we hold true to Windfall’s core values: (1) Be an excellent communicator; (2) Operate with transparency; (3) Provide leverage, not optimization; (4) Make a difference every day; and (5) Act with integrity and trust. If you are a driven, detail-oriented data scientist with experience in model risk management (OCC standards), who thrives on building and deploying complex machine learning models at scale, we’d love to hear from you.
Responsibilities:
Model Training & Deployment : Lead the training and production deployment of Windfall’s foundational models, focusing on predicting key financial metrics like household net worth and investable assets.
Model Performance Analysis : Analyze and monitor the performance of machine learning models, ensuring they meet business goals and adhere to model risk management standards.
Documentation & Communication : Document modeling processes with a high level of rigor and transparency. Effectively communicate key performance metrics and model insights to business stakeholders, ensuring clarity and alignment.
Model Risk Management : Ensure compliance with OCC Model Risk Management standards, implementing processes for model validation, testing, and monitoring.
Data Handling : Work with large, disparate sources of data to build robust and stable models that are resilient in real-world applications.
Cross-Functional Collaboration : Partner closely with engineers, analysts, and business stakeholders to design and implement models that deliver actionable insights and drive business outcomes.
Requirements:
At least 8 years experience working directly with machine learning models.
Advanced proficiency in machine learning techniques and statistical modeling.
Expert in Python, with a strong track record of building, deploying, and maintaining machine learning models at scale.
Experience handling large, diverse datasets from multiple sources.
Impeccable attention to detail in both model development and result reporting.
Strong ability to communicate technical concepts and complex model outputs clearly and effectively to non-technical stakeholders.
Preferred Qualifications:
Advanced degree (Master’s or PhD) in Data Science, Machine Learning, Statistics, Computer Science, or related fields.
Experience specifically with predictive models for financial products (e.g., household net worth, investable assets, credit scoring).
Experience with OCC model risk management practices, and working within highly regulated environments.
Proven experience in putting large-scale machine learning models into production environments.
Understanding of financial regulations and compliance, particularly around model risk management standards (e.g., OCC regulations).
Familiarity with MLOps tools and processes to monitor and manage machine learning models in production.
Salary Information:The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across California. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. We also offer a comprehensive benefits package, which you can explore on our careers site.
California : Salary range is $225K - $350K which will include a bonus component.
Compliance:We comply with CCPA. For more information on how we comply, review our privacy notice.
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We’re on a mission to change how organizations perceive and use people data - and we hold true to Windfall’s core values: (1) Be an excellent communicator; (2) Operate with transparency; (3) Provide leverage, not optimization; (4) Make a difference every day; and (5) Act with integrity and trust. If you are a driven, detail-oriented data scientist with experience in model risk management (OCC standards), who thrives on building and deploying complex machine learning models at scale, we’d love to hear from you.
Responsibilities:
Model Training & Deployment : Lead the training and production deployment of Windfall’s foundational models, focusing on predicting key financial metrics like household net worth and investable assets.
Model Performance Analysis : Analyze and monitor the performance of machine learning models, ensuring they meet business goals and adhere to model risk management standards.
Documentation & Communication : Document modeling processes with a high level of rigor and transparency. Effectively communicate key performance metrics and model insights to business stakeholders, ensuring clarity and alignment.
Model Risk Management : Ensure compliance with OCC Model Risk Management standards, implementing processes for model validation, testing, and monitoring.
Data Handling : Work with large, disparate sources of data to build robust and stable models that are resilient in real-world applications.
Cross-Functional Collaboration : Partner closely with engineers, analysts, and business stakeholders to design and implement models that deliver actionable insights and drive business outcomes.
Requirements:
At least 8 years experience working directly with machine learning models.
Advanced proficiency in machine learning techniques and statistical modeling.
Expert in Python, with a strong track record of building, deploying, and maintaining machine learning models at scale.
Experience handling large, diverse datasets from multiple sources.
Impeccable attention to detail in both model development and result reporting.
Strong ability to communicate technical concepts and complex model outputs clearly and effectively to non-technical stakeholders.
Preferred Qualifications:
Advanced degree (Master’s or PhD) in Data Science, Machine Learning, Statistics, Computer Science, or related fields.
Experience specifically with predictive models for financial products (e.g., household net worth, investable assets, credit scoring).
Experience with OCC model risk management practices, and working within highly regulated environments.
Proven experience in putting large-scale machine learning models into production environments.
Understanding of financial regulations and compliance, particularly around model risk management standards (e.g., OCC regulations).
Familiarity with MLOps tools and processes to monitor and manage machine learning models in production.
Salary Information:The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across California. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. We also offer a comprehensive benefits package, which you can explore on our careers site.
California : Salary range is $225K - $350K which will include a bonus component.
Compliance:We comply with CCPA. For more information on how we comply, review our privacy notice.
#J-18808-Ljbffr