Who We Are

Yieldmo is one of the worlds fastest-growing digital advertising & attention analytics companies. Agencies & brands use its premium marketplace to create, measure, model, & optimize their campaigns for unmatched scale & performance. Underpinned by AEROS Attention Analytics, advertisers can now truly understand how consumers are interacting with ads before the click, & after the initial view. Yieldmo ultimately delivers better results by harnessing the power of attention data to drive superior audience engagement & targeting. 

What We Need

We are looking for a data scientist to develop optimization models to enhance our marketplace. You will use statistical analysis, machine learning, & optimization techniques to help answer questions such as, what is the propensity for a buyer to purchase an ad impression & what price will the buyer pay for the ad impression. You will be part of a team of data scientists & engineers that is focused on increasing yield to sellers on our marketplace while ensuring that buyers performance objectives are met. You will use a cutting-edge cloud technology stack to work with a dataset comprising billions of daily records & petabytes of storage, & make hundreds of millions of predictions deployed to environments requiring milliseconds response times.

Responsibilities

• Develop models that help predict the value of an ad impression on our marketplace.
• Perform large-scale data analysis & develop optimization algorithms.
• Predictive analytics & modeling.
• Machine learning with high dimensionality.
• Statistical data modeling & analysis.

Requirements

• At least 5+ years experience working as a data scientist.
• A passion for innovating with data science at scale applying modern algorithms to massive datasets & creating measurable business value.
• Must be able to develop working prototypes, prove that they add meaningful value, & ensure that they are implemented properly in a production environment.
• Excellent understanding of algorithms, scalability, & various tradeoffs in a big data setting.
• Strong verbal & written communication skills.
• Comfortable working with onshore & offshore distributed teams.
• Strong expertise in at least one language for data manipulation, analysis, & machine learning, such as Python, R, or Matlab, interacting with distributed computing resources.
• Experience in querying & manipulating data with SQL or another data query language in a big data environment.
• MS or equivalent combination of education & experience.

Nice to Haves

• Ad tech experience (SSPs, DSPs, Analytics, DMPs, CDPs).
• Intermediate-level programming experience with Python.
• Microservices architectures experience.
• Exposure to Snowflake & Looker or similar platforms.
• Exposure to high-volume low-latency environments.
• Exposure to AWS or Google Cloud.

Perks

• Home office setup stipend.
• 2 Mental Escape (ME) days each month.
• Learning stipend & professional development opportunities.
• Work-life balance, flexible PTO, & competitive compensation packages.