The company is looking to solve the problem of driving data-informed solutions in marketing analytics, specifically in areas such as experimentation, automation, and data science.
Requirements
- Expertise in at least one scripting language (ideally Python/R), with experience building models in either language
- Proficiency in SQL and Hive.
- Strong background in statistical analysis, programming, and experimentation.
- Experience in querying and manipulating large data sets.
- Knowledge to translate quantitative findings into actionable insights and influence business decisions.
- Meaningful time as a data scientist partnering with business functions, ideally with paid marketing teams, and having expertise in analyzing brand campaigns.
- Ability to draw on experience to identify where data can have the most impact and clearly communicate findings and recommendations to partner teams.
Responsibilities
- Develop data-driven insights to drive marketing decisions and improve business outcomes.
- Utilize models and develop advanced experimentation methods, such as synthetic controls, propensity score matching techniques etc. to measure marketing's impact across our suite of products.
- Utilize time-series forecasting models to predict growth and set the right growth goals, and develop frameworks to implement marketing attribution models.
- Design, launch, and analyze experiments to understand the incrementality of different messaging and creative campaigns.
- Design measurement approach and identify flaws in experiment practices and results, especially in 3P environments.
- Manage data integration and engineering with marketing technology platforms for data hygiene, segmentation, and targeting.
- Apply expertise in data mining and data presentation, as well as knowledge of marketing channels and platforms, to identify opportunities.
Other
- Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, or related field or equivalent experience
- 3+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data.
- Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership teams.
- Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions.
- Ability to make tradeoffs between speed and accuracy wisely
