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 leading performance-focused connected TV (CTV) advertising technology company provides a purpose-built platform for performance marketers. The organization leverages large-scale data and advanced data science to automate and optimize television advertising, helping advertisers achieve measurable business outcomes.
Its platform brings together media buying, optimization, measurement, and attribution into an integrated solution. Built by experienced professionals in programmatic advertising, digital media, and ad verification, the platform is designed to provide advertisers with reliable and scalable CTV performance capabilities.
The organization is seeking a Sr. Data Scientist to join its Data Science team and transform complex data into actionable insights that support business decisions. The role will involve owning analytics projects from inception through completion, developing customized reporting and analytics tools, and translating analytical findings into data science products.
The successful candidate will work closely with data science teams, customers, and stakeholders while developing production-quality solutions that improve advertising campaign performance. The position requires strong statistical and machine learning fundamentals, production-level Python development skills, and the ability to work effectively in a fast-growing and experimental environment.
Key Responsibilities
- Write and maintain production-level code in Python.
- Design, launch, and analyze experiments to optimize advertising campaigns.
- Develop reporting and analytics tools tailored to customer and stakeholder requirements.
- Transform insights generated through reporting and analytics tools into data science products.
- Own analytics projects from initial concept through implementation and completion.
- Translate effectively between Data Science Analytics and Data Science Product teams.
- Provide high-quality analytical support and service to customers and stakeholders.
- Use data-driven insights to support business decisions and improve advertising performance.
- Collaborate with cross-functional teams in an environment characterized by rapid growth, experimentation, and continuous iteration.
- Apply AI tools responsibly to improve the speed and quality of day-to-day analytical workflows.
Required Qualifications
- Ability to write and review production-level Python code.
- Strong foundation in statistics and machine learning.
- Experience defining and measuring the utility of reporting and analytics tools.
- Ability to quickly translate requirements and insights between Data Science Analytics and Data Science Product teams.
- Strong track record of delivering high-quality service to customers and stakeholders.
- Bachelor’s degree in computer science, statistics, a related field, or equivalent professional experience.
- Ability to work effectively in an environment involving ambiguity, ownership, product scaling, experimentation, and iterative development.
- Demonstrated ability to use AI to improve the speed and quality of relevant professional outputs.
- Strong ability to critically evaluate and verify AI-assisted work through testing, source-checking, data validation, peer review, and other quality-control practices.
- High integrity and ownership, including responsible handling of sensitive data and accountability for final decisions and deliverables.
Preferred Qualifications
- Experience in advertising technology (AdTech) or connected TV (CTV).
- Big data experience with Scala, Apache Spark, Apache Beam, and AWS Athena.
- Experience developing analytics solutions for advertising or media platforms.
- Experience working with large-scale datasets and production data science systems.
- Experience applying experimentation and statistical analysis to optimize business outcomes.
- Strong ability to operate effectively in a fast-growing technology environment.
AI and Data Responsibility
- Demonstrated ability to use AI as a productivity and analytical aid while maintaining professional judgment.
- Strong track record of critically evaluating AI-generated or AI-assisted outputs.
- Experience validating data, testing analytical results, checking sources, and conducting peer reviews.
- Commitment to protecting sensitive information and preventing inappropriate reliance on AI.
- Accountability for the accuracy, quality, and integrity of final decisions and deliverables.
Disclaimer
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- No Client Relationship: This company is not a client of SpringCube unless stated.
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