Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A global visual discovery and inspiration platform connects millions of people around the world with creative ideas, new possibilities, and ways to plan meaningful experiences. The organization focuses on innovation, creativity, and building products that help people discover and create a life they love.
The company also places a strong emphasis on artificial intelligence as a partner that augments creativity and increases impact. Its teams work with AI to improve products, accelerate decision-making, and create new opportunities while maintaining a strong focus on foundational technical and analytical skills.
The organization is seeking a Sr. Data Scientist, Monetization to join its Monetization Engineering organization. This role will take end-to-end ownership of designing, researching, building, and delivering data products while collaborating with cross-functional teams to formulate, experiment with, and evolve advertising strategies.
Key Responsibilities
- Conduct deep strategic analysis to answer complex questions related to advertising ecosystem metrics and performance.
- Evaluate trade-offs between metric changes and assess the overall impact of changes across different components of the advertising ecosystem.
- Perform opportunity sizing and analysis to identify areas for growth and investment.
- Develop clear and actionable analyses that help teams identify areas for improvement and prioritize investments.
- Build segmentation models to assess supply and inform pricing strategies.
- Improve decision-making speed and quality through experimentation, causal inference, and other data science methodologies.
- Design measurement strategies and advise teams on experimentation best practices.
- Identify weaknesses or flaws in experimental practices and results and develop tools to improve experiment analysis.
- Create and monitor success metrics for engineering teams.
- Break down high-level metrics into actionable segments to identify specific areas of improvement.
- Develop new datasets and analytical resources when required to support business and engineering objectives.
- Build dashboards and monitoring systems to track critical components of business metrics.
- Monitor data quality, including missing values, implausible values, and duplicate data across advertisers and over time.
- Lead and mentor data scientists working within the same area.
- Demonstrate high-quality analytical output while supporting the development and performance of other team members.
- Provide continuous and constructive feedback, recognize individual strengths and contributions, and identify opportunities for improvement.
- Collaborate with cross-functional teams to translate analytical findings into actionable business and product strategies.
Required Qualifications
- Bachelor’s or Master’s degree in Data Science or another relevant quantitative field, or equivalent practical experience.
- 5+ years of combined postgraduate academic and industry experience applying scientific methods to solve real-world problems using large-scale data.
- Strong foundational knowledge of statistics and experimentation.
- Proven ability to apply scientific methodologies to complex real-world problems involving web-scale datasets.
- Strong analytical and problem-solving skills.
- Proficiency in SQL, Hive, and Python.
- Experience working with large-scale data and developing data-driven solutions.
- Strong communication skills and the ability to clearly explain analytical approaches, findings, and recommendations.
- Ability to collaborate effectively with cross-functional teams.
Preferred Qualifications
- Domain knowledge of advertising ecosystems, digital advertising, or real-time bidding.
- Experience with experimentation and causal inference techniques.
- Experience designing measurement frameworks for engineering or product organizations.
- Experience building analytical tools, dashboards, and monitoring systems.
- Experience mentoring or providing technical leadership to other data scientists.
- Strong understanding of advertising metrics, monetization strategies, and pricing optimization.
- Ability to use data science techniques to influence strategic business decisions.
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