Overview
The Data Scientist will be instrumental in supporting a leading consumer business in analyzing complex customer data to drive strategic initiatives in retention, segmentation, and pricing. This hybrid role requires engagement with messy, real-world datasets and collaboration with team members to implement effective data solutions. The position entails a significant level of autonomy in determining methodologies and approaches to deliver impactful insights, especially in preparation for a peak trading season.
Responsibilities
- Analyze and interpret complex customer data to drive actionable insights.
- Develop predictive models to support customer segmentation and retention strategies.
- Collaborate with stakeholders to identify key data needs and project objectives.
- Utilize Python and SQL to manipulate and extract meaningful information from raw datasets.
- Contribute to the design and implementation of data processes using platforms like Databricks, Snowflake, or Azure Synapse.
- Effectively communicate findings and recommendations to non-technical stakeholders.
- Adapt methods and approaches in response to project requirements and data challenges.
Requirements
- Proven ability in Python and SQL for data analysis and model building.
- Experience with data platforms such as Databricks, Snowflake, or Azure Synapse.
- Strong background in customer segmentation, churn analysis, or predictive modeling.
- Ability to navigate ambiguity and establish processes in a dynamic environment.
- Demonstrated track record of shaping data strategies and methodologies independently.
- Experience in a consumer-focused business environment is preferred.