The company is looking to solve complex business problems and improve performance through advanced machine learning, statistical, economic, and optimization approaches.
Requirements
- Strong knowledge of experimental design and analysis
- Expertise in causal inference, statistical analysis and testing, and model development
- Ability to use a programming language like Python or R to work efficiently at scale with large data sets
- Proficiency in SQL, Hive, and Spark for data manipulation and analysis
- Machine learning
- Statistics
- Operations Research
Responsibilities
- Develop creative solutions and build prototypes to business problems using algorithms based on machine learning, causal inference, statistics, and optimization.
- Collaborate with engineering and product teams to productionize these solutions and create a lasting impact.
- Drive clarity and solve ambiguous, challenging business problems using data-driven approaches, with an emphasis on understanding causal relationships when applicable.
- Propose and guide robust frameworks of data analysis to drive business insights and inform decision-making.
- Establish standard methodologies for data science, including modeling, coding, analytics, and experimentation.
- Leverage data to understand product performance and identify improvement opportunities, including analyzing potential causal factors.
- Design product experiments and interpret results to draw detailed and impactful conclusions.
Other
- Bachelor’s degree in Statistics, Machine Learning, Operations Research, Economics, Computer Science, or another related field
- 5 years of related experience
- Master’s or Ph.D. in Statistics, Machine Learning, Operations Research, Economics, Computer Science, or a related field
- Communicate findings and insights to senior management and cross-functional teams
- Provide recommendations to assist quick product ideation and feature launch decisions
