Data Scientist at Capital One creating machine learning models for customer management. Collaborating with teams to deliver insights from large datasets to enhance customer decisions.
About the role
- Data Scientist developing machine learning solutions and analytics capabilities for casino clients. Collaborating with data engineers and product teams to optimize operations.
Responsibilities
- Build and maintain statistical models, machine learning algorithms, and predictive analytics using gaming and behavioral data (segmentation, churn prediction and lifetime value models)
- Create anomaly detection systems for fraud and compliance monitoring
- Collaborate with data engineers to collect and preprocess data, and build and maintain data pipelines
- Design A/B testing frameworks and experiment analyses to test hypotheses and measure the effectiveness of solutions
- Document models and use data visualization tools to communicate insights and findings to stakeholders
Requirements
- BS/MS in a quantitative field or equivalent experience; years of experience commensurate with level
- Strong Python programming skills and proficiency in SQL for data extraction and analysis
- Strong foundation in statistics and experimentation: hypothesis testing, probability distributions, regression analysis, metric design, etc.
- Experience with machine learning frameworks (scikit-learn, pandas) and deep learning libraries (PyTorch or TensorFlow), along with fundamental ML concepts (model evaluation, cross-validation, feature engineering)
- Strong communication and story-telling skills, and ability to work collaboratively with cross-functional teams
- Intellectual curiosity and comfort with ambiguity; we're building new things, not following playbooks.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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