Identifying growth opportunities: Assisting in the generation, prioritization, validation, and evaluation of hypotheses ('what would happen if...?') to improve key product metrics.
Conducting A/B tests: Evaluating the impact of changes using A/B tests and causal inference techniques.
Monitoring key product metrics: Identifying the causes of anomalies and deviations in key metrics, and signaling potential issues with the product.
Maintaining dashboards: Creating, updating and improving product dashboards.
Collaborating with cross-functional teams: Work closely with data scientists, software engineers, and product managers to integrate AI solutions into the overall product pipeline.
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