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We are seeking a highly skilled and experienced Data Scientist to join our CS Analytics team at Hopper. The ideal candidate will have a strong background in SQL, Python, GCP, Airflow, Tableau, Amplitude, and Data Science, focusing on Natural Language Processing (NLP).
Key Responsibilities- Frame and perform complex exploratory analyses to enhance our understanding of Hopper users, focusing on key drivers of conversion, retention, and overall user engagement.
- Manage the entire data science lifecycle from data extraction, transformation, and analysis to model development and deployment, collaborating closely with product, engineering, and operations teams to deliver customer-centric products.
- Apply advanced data science principles, particularly in NLP, to support ongoing projects, providing insights from unstructured data sources.
- Develop and maintain sophisticated dashboards for tracking product experiments, monitoring business unit performance, and analyzing key metrics using tools like Amplitude, Tableau, and BigQuery.
- Translate complex analytical findings into clear, actionable insights that non-technical stakeholders can easily understand, ensuring alignment across teams and facilitating data-driven decision-making.
- Extensive experience with SQL for relational database management and complex querying.
- Proficiency in Python for large-scale data preparation, analysis, and model development.
- Strong experience with data mining, machine learning, and statistical modeling tools, including underlying algorithms.
- Proven ability to build and manage data pipelines using Airflow on Google Cloud Platform, ensuring data quality, consistency, and accessibility.
- Proficiency in business reporting tools such as Tableau and Amplitude for data visualization and event-based analytics.
- Extremely strong analytical and problem-solving abilities, focusing on breaking down complex business problems to identify key data drivers.
- Extensive experience conducting empirical research and answering challenging questions with data-driven approaches.
- Proven ability to translate complex technical findings into clear, actionable insights for non-technical stakeholders.
- Strong ability to communicate models and insights effectively to technical and non-technical audiences.
- Comfortable collaborating with engineering teams to identify, implement, and own data science solutions in production environments.
- Ability to create ETL pipelines and/or support engineering teams in their creation and maintenance.
- Experience in the travel or hospitality industry is a plus.
- Familiarity with Unix/Linux environments.
- Experience with revenue management models and practices in the travel industry.
