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Senior Data Scientist
Job description
We’re looking for someone who loves to build, learn, and guide others. You’ll be working closely with our client's CEO/COO and other clients, so clear communication and a collaborative spirit are key.
How You'll Contribute
- Business Insight & Problem Definition: Partner closely with marketing and product teams to diagnose business challenges and define appropriate data metrics, analyses, and interpretations to drive strategic decisions.
- Statistical Modeling: Define requirements for and lead the creation, monitoring, and iterative improvement of key statistical models used for marketing spend optimization and product growth.
- Narrative & Visualization: Design clear, unambiguous narratives and data visualizations to communicate model outputs and analysis results to broad, non-technical audiences.
- Rapid Prototyping: Independently prototype and test new insights, moving from hypothesis to rigorous validation with minimal mentorship.
- Technical Consultation: Reason effectively about the strengths and weaknesses of different modeling approaches, selecting and iterating on combinations that suit specific marketing contexts.
We're Looking for Someone Who...
- Has Senior-Level Impact: You are a high-level individual contributor who works with significant independence to lead complex data science initiatives that impact the Core Tech roadmap.
- Is a Creative Problem Solver: You are solution-oriented, a self-starter, and have the ability to build compelling narratives from raw data.
- Drives Strategic Influence: You have the ability to work across all levels of the organization to influence product and marketing strategy through data-backed evidence.
Requirements
- Programming & Libraries: Expert proficiency in Python or R for sophisticated multi-dimensional data sets (specifically libraries like CausalImpact and RStan).
- Data Carpentry: Advanced SQL skills to confidently manipulate and structure data.
- Cloud Experience: Hands-on experience working across major cloud providers (AWS, Azure, GCP).
- Data Platforms (Nice to have): Familiarity or experience working within Databricks.
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