Who We Are
Verve has created a more efficient and privacy-focused way to buy and monetize advertising. Verve is an ecosystem of demand and supply technologies fusing data, media, and technology together to deliver results and growth to both advertisers and publishers–no matter the screen or location, no matter who, what, or where a customer is. With 13 offices across the globe and with an eye on servicing forward-thinking advertising customers, Verve’s solutions are trusted by more than 90 of the United States’ top 100 advertisers, 4,000 publishers globally, and the world’s top demand-side platforms. Learn more at www.verve.com.
We are seeking a Senior ML Engineer to join our growing team. This role will be based in our Bangalore, India office.
As Verve brings the capabilities of all players in the ad tech ecosystem (SSPs, Exchange, DSPs, and DMPs) under one umbrella, our Data Science Research currently follows two major tracks covering different aspects:
Audience-focused, which includes segmenting users for targeting and market research
Exchange-focused, which includes optimizing the flow of traffic between supply and demand partners and maximizing revenue
What You Will Do
DOMAIN
In this role your main focus would be on our Ad-Exchange Optimization projects
Win Price Prediction in various auctions setups - 1st price, 2nd price, Waterfall
Supply forecasting — Modeling time dependent supply availability,
Demand forecasting — Modeling time dependent demand interest,
Inventory valuation — Assessing true value of inventory in open market,
Traffic Shaping — Time dependent supply and demand matching.
Our Machine Learning Engineer role includes the following responsibilities:
Designing, developing, and researching cutting edge Machine Learning systems, models, and schemes in many different areas of Adtech
Developing real-time algorithms for exchange optimization
Discovering insights/patterns in exchange data, and developing methods to leverage/extract/process/analyze complex, high volume, high-dimensional datasets
Designing experiments, overseeing A/B testing, evaluating the quality of derived assets, and developing dashboards to continuously monitor model performance
Studying, transforming, and converting data science prototypes,
Searching and selecting appropriate data sets
Performing statistical analysis and using results to improve models
Training and retraining ML systems and models as needed
Identifying differences in data distribution that could affect model performance in real-world situations
Visualizing data for deeper insights
Analyzing the use cases of ML algorithms and ranking them by their success probability
Understanding when your findings can be applied to business decisions
Reducing business problems into optimization problems
Supporting, maintaining, and enriching existing ML frameworks and libraries
Verifying data quality and/or ensuring it via data cleaning
Work closely with product, engineering, and sales teams to drive the use of Data Science across Verve
Collaborate with our audience-focused Data Science team
Design end-to-end Data Science Products, working closely with the data and backend engineering teams
Collaborate with teams across the globe in different time zones
Extend successful solutions and optimization to sister companies in Verve
