Data Scientist

About Fever

Fever is the leading global live-entertainment discovery platform that helps millions of people enjoy the best experiences in their cities. With a mission to democratize access to culture and entertainment, Fever inspires its users to explore unique local experiences, from immersive exhibitions, interactive theater, and festivals to molecular cocktail pop-ups. Through its platform, Fever has transformed the way people discover and engage with their cities, fostering a vibrant community of experience-seekers worldwide.

Fever is seeking a talented and passionate Data Scientist to join our growing data team. In this role, you will be instrumental in building and deploying data products that drive key business decisions and enhance user experiences. You will leverage your expertise in statistical modeling, machine learning, and experimentation to extract actionable insights from our rich datasets and contribute directly to Fever's success.

• Design, develop, and deploy predictive models and machine learning algorithms to optimize various aspects of our business, including recommendations, pricing, and user engagement.
• Conduct in-depth statistical analysis to uncover trends, identify opportunities, and measure the impact of product changes and marketing initiatives.
• Design and analyze A/B tests and other experiments to evaluate new features and strategies, providing data-driven recommendations.
• Collaborate closely with product managers, engineers, and other stakeholders to translate business problems into data science solutions.
• Communicate complex analytical findings and recommendations clearly and effectively to both technical and non-technical audiences.
• Contribute to the development and improvement of our data infrastructure and tools.

• 3+ years of experience as a Data Scientist
  , preferably in a fast-paced, product-driven environment.
• Strong proficiency in Python and its data science libraries (e.g., pandas, scikit-learn, Num Py).
• Expertise in SQL for data extraction, manipulation, and analysis.
• Solid understanding of statistical modeling, hypothesis testing, and experimental design (A/B testing).
• Experience with machine learning techniques, including regression, classification, clustering, and recommendation systems.
• Ability to perform feature engineering and work with large, complex datasets.
• Excellent communication and presentation skills, with the ability to tell stories with data.
• Strong problem-solving skills and a proactive approach to identifying and addressing business challenges.
• Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline.