VP, Data Science

New York, NY
Diply VP of Data Science, Machine Learning and AI, will have the opportunity to build a superstar data science team from the ground up, both setting the strategy and ensuring tactical execution.

 

You will partner with business stakeholders to identify and prioritize top Data Science and AI opportunities, create business/technical requirements, transform over 50B monthly records of data into scientific models and AI-driven solutions, lead ML strategy and roadmap planning, and build out the data science and AI teams. The ideal leader will combine expert Data Science/AI/ML knowledge with hands on experience building algorithms/models/programming and outstanding management skills in managing teams and delivering complex/critical projects.  Media industry experience is an asset.

 

Major Responsibilities:

 

·         Develop and maintain consultative relationships with key business stakeholders, proactively identifying data analytics needs to meet business requirements.  Some initial deliverables are listed below.

 

·         Provide strategic guidance to the data infrastructure team with respect to acquiring and warehousing various data from our sources (including Google Analytics, Google DFP, Headerbid Ad Network Raw Data, Facebook Insights and Ad Data, etc).

 

·         Develop a standard process to define data requirements, manage governance, and create data analytics solutions for use throughout the organization.

 

·         Recruit and hire a Data Science Team and AI/ML Team

 

Some of the Data Science/ML/AI Projects you would spearhead are listed below:

 

·         Develop a model to determine unique users coming to our website in real-time.  This will allow us to identify  users are coming to our site.  The unique user ID will be used to tie our various raw data sets together (including Google Analytics Raw Data, Google DFP Raw Data, Headerbid Ad Network Raw Data, etc)

 

·         Develop a content recommendation model (AI/ML) for our users allowing customized  article recommendations based on user characteristics.  The content recommendation model should increase user engagement and revenue.  This will involve understanding our content and related taxonomy, user characteristics, social media insights  among other factors in order to determine which content to recommend next to users.

 

·         Develop models to predict content performance on various social media platforms (Facebook, Instagram, Pinterest, Twitter, etc.) in order to increase user engagement and reach.

 

·         Develop a model to predict in real-time the value of a user on our website from a digital advertising perspective (factors determining this would include time of day, user demographics, previous interactions, article type, real-time ad revenue data from our headerbid networks, estimated revenue from Google Ad Ex ad networks, estimated session length, etc.) in order to predict in real-time the value of user on our website).

 

Benefits

Full benefit package including Health, Dental, Short Term and Long Term Disability.

Requirements

·         Master’s in Engineering, Computer Science, Mathematics, Computational Statistics, Operations Research, Machine Learning or related technical fields.   ·         Proven track record of strong verbal/written communication and presentation skills, including an ability to effectively communicate with both business and technical teams.   ·         Excellent planning, project management, leadership, and talent management skills.   ·         Experience in projects involving large scale-multi dimensional databases, complex business infrastructure, and cross-functional teams.   ·         Hands on experience developing machine learning algorithms using relevant programming languages, and big data tools. Experience in evaluating and making decisions around the use of new or existing tools for a project.   ·         Extensive experience with advanced ML techniques (neural networks/deep learning, reinforcement learning, SVM, PCA, etc.).   ·         Experience with open source technologies, ML libraries, and programming languages.   ·         Experience building and delivering complex systems that leverage various machine learning algorithms or technologies that integrate well with other organization-wide systems and are able to scale effectively.   ·         Experience with Google Big Query and Microsoft Cosmos an asset.   ·         Proficiency with adtech (Google DFP and headerbid networks) and adtech empowering tools like DMPs, DSPs, automation and machine learning solutions, and analytics modeling is an asset.   ·         Proficiency with user analytics (age, gender, demographics, etc) with tools such as Google Analytics and Comscore, Facebook Analytics, and other social media platforms is an asset.   ·         Media, Advertising, E-Commerce, or Consulting industry experience a plus.  
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