TTD is looking to improve the buying strategy by developing metrics to quantify supply path efficiency and applying scalable data science modeling on large-scale datasets.
Requirements
- Proficient in open-source languages, you have a strong passion for enhancing and expanding your technical skills. Your expertise includes hands-on development of statistical models and solutions utilizing open-source tools and cloud computing platforms. Has a deep understanding of the foundations of statistics, applied mathematics, and experimentation.
- Hands-on experience building data science solutions at scale.
- Strong background in causal inference and experimental design in production environments.
- Proficiency in Python and Scala
- Hands-on experience running large-scale workloads on distributed computing clusters (e.g., EMR, Databricks), leveraging Spark to process big datasets.
- Experience in programmatic advertising and/or real-time auctions is a plus.
- Experience with deep learning is a plus.
Responsibilities
- Develop and apply causal inference methodologies to measure the efficiency of supply paths, leveraging techniques such as double machine learning, instrumental variables, propensity scoring, and synthetic control methods.
- Define success criteria for causal measurement and ensure that model insights translate into tangible business improvements.
- Design and analyze experiments (e.g., A/B tests) to validate model performance
- Develop algorithms and models to proactively detect and interpret shifts in inventory supply paths.
- Collaborate with product managers and engineers to integrate models into existing workflows, making outputs actionable and aligned with business objectives.
- Mentor junior data scientists, fostering growth, technical excellence, and knowledge-sharing across the team.
Other
- A track record of owning a project end-to-end (from research to production), and partnership with a cross-functional team of data scientists, engineers, and product managers to deliver advanced analytics or models.
- Possess a keen sense of data intuition and the ability to innovate in the field of metric development, control systems, causal inference, and/or statistical modeling, as evidenced by achievements like first-author publications or project successes.
- BS/MS with 6+ years of experience, or PhD with 4+ years of experience, in a data science role involving the full product lifecycle from ideation to production.
- Excellent communication skills, with the ability to engage diverse stakeholders, make architectural recommendations, drive effective execution, and measure outcomes.
