Remote Data Scientist Job in United States Hopper

Who you are

• 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.

What the job involves

• 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.