Senior Data Scientist-Measurement

The Trade Desk is a global technology company with a mission to create a better, more open internet for everyone through principled, intelligent advertising. Handling over 1 trillion queries per day, our platform operates at an unprecedented scale. We have also built something even stronger and more valuable: an award-winning culture based on trust, ownership, empathy, and collaboration. We value the unique experiences and perspectives that each person brings to The Trade Desk, and we are committed to fostering inclusive spaces where everyone can bring their authentic selves to work every day. 

Do you have a passion for solving hard problems at scale? Are you eager to join a dynamic, globally connected team where your contributions will make a meaningful difference in building a better media ecosystem? Come and see why Fortune magazine consistently ranks The Trade Desk among the best small-medium-sized workplaces globally. 

ABOUT THE ROLE 

Data scientists at TTD work closely with engineering throughout the lifecycle of the product, from ideation to production and monitoring. Our data scientists are end-to-end owners. You will participate actively in all aspects of designing, researching, building, and delivering data-focused products for our clients and traders. 

This particular role is responsible for research and application of state-of-art modeling techniques to solve measurement problems centered around Advertising Technology. This role will collect and explore data, research into methodologies, design experiments to validate model results, and implement research work in production. This role will be able to work across all methods of measurement in AdTech, but will have a particular focus on helping to move both internal and external clients towards more sophisticated measurement solutions that prove the causal impact of ads served by the TTD platform. The work of this role will help to build out and make causal lift more accessible and attainable on our platform. 

The main job directions include: 
-Explore, evaluate and deploy models to solve the problem of “Are TTD ads driving incremental lift?” 

-Help to define and build methods to optimize towards causal effects
-Explore data from various sources within TTD and prototype ETL pipelines to collect them for model training. 

- Design and analyze experiments (e.g. A/B test) to validate model results. 
- Work with cross-functional stakeholders to come up with the best implementation and testing plan. 

- Communicate learnings from data and insights from models in compelling ways to influence product decisions. 

WHO WE ARE LOOKING FOR  

• 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 and machine learning models and solutions utilizing open-source tools and cloud computing platforms. Has a deep understanding of the foundations of statistics and machine learning models. 
• Hands-on experience building models at scale. 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.
• Possessing a keen sense of data intuition and the ability to innovate in the field of causal inference and/or machine learning, as evidenced by achievements like first-author publications or project successes.

WHAT YOU BRING TO THE TABLE 

We do not expect you to know every technology we use when you start at TTD. What we care most about is that you can learn quickly and solve complex problems using the best tools for the job. However, we find that the most successful candidates typically come in with something like the following experience: 

• BS/MS with 4+ years or a PhD with 2+ years of experience working in a DS or ML role that involves bringing products from ideation to production.
• Experience in causal inference and lift measurement
• Experience of designing experiments in a production environment.
• Proficient in Python. 
• Experience in programmatic advertising is a plus
• Experience running heavy workloads on a distributed computing cluster (especially EMR or Databricks), leveraging technologies like Spark to work with large datasets preferred.
• The ability to communicate with diverse stakeholders, making architecture recommendations, ensuring effective execution, and measuring quality of outcomes.