Data Science Intern working on computer vision for Johnson & Johnson's Innovative Medicine. Collaborating in a pharmaceutical environment to develop deep learning models for medical imaging.
About the role
- Staff Data Scientist designing and building scalable machine learning systems for Windfall, a people intelligence and AI company. Tackling complex problems and collaborating with customers on innovative modeling solutions.
Responsibilities
- 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.
Requirements
- 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.
Benefits
- Additional 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.
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