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ABOUT RINGABOUT THE ROLEKey job responsibilities
- Drive shared understanding among business, engineering, and science teams of domain knowledge of processes, system structures, and business requirements.
- Lead development and validation of state-of-the-art technical designs (data pipelines, data models, causal inference, predictive models, data insights/visualizations, etc)
- Contribute to the hiring and development of othersA day in the life
Translate/Interpret
• Complex and interrelated datasets describing customer behavior, messaging, content, product design and financial impact.Measure/Quantify/Expand
• Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
• Analyze historical data to identify trends and support decision making.
• Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
• Provide requirements to develop analytic capabilities, platforms, and pipelines.
• Apply statistical or machine learning knowledge to specific business problems and data.Explore/Enlighten
• Formalize assumptions about how users are expected to behave, create statistical definition of the outlier, and develop methods to systematically identify these outliers. Work out why such examples are outliers and define if any actions needed.
• Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.
• Make decisions and recommendations.
• Build decision-making models and propose solution for the business problem you defined.
• Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.
• Utilize code (Python/R/SQL) for data analyzing and modeling algorithms.
- Bachelor's degree
- 4+ years of data scientist experience
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- Experience with statistical models e.g. multinomial logistic regression
- 5+ years of hands-on experience in modeling and analysis, and in deploying machine learning / deep learning models in production.
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