We're seeking a highly skilled and experienced Data Scientist to join our CS Analytics team. The ideal candidate will have a strong background in SQL, Python, GCP, Airflow, Tableau, Amplitude, and Data Science, focusing on Natural Language Processing (NLP). We are looking for someone who has demonstrated experience in a reputable organization and aligns with our company culture. This role requires someone capable of handling complex data challenges, building and maintaining data pipelines, and providing actionable insights to drive business decisions. You may be a great fit for our team if you're a curious self-starter who thrives in ambiguity, is passionate about exploring the intersection of real business problems with huge (and often messy) data sets, and finding effective ways to simplify and focus on practical opportunities to deliver significant value to our customers. What would your day-to-day look like 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. An ideal candidate has 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. Preferred Qualifications 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. Perks and benefits of working with us: Well-funded and proven startup with large ambitions, competitive salary. Hopper offers group medical and dental insurance to full-time employees. Hopper offers life insurance with short term and long term disability coverage. All employees and dependents have access to telemedicine services, anytime, anywhere. Please ask us about our very generous parental leave, much above industry standards! Unlimited PTO. Carrot Cash travel stipend. Flexdesk Access Pass & Work-from-home stipend. Entrepreneurial culture where pushing limits and taking risks is everyday business. Open communication with management and company leadership. Small, dynamic teams = massive impact. #J-18808-Ljbffr
