Media Delivery Specialist

Job Description

About This Role: 

The Media Delivery team is responsible for operating our cutting-edge technology platform, making real-time media investment decisions to drive client campaign performance and returns on ad spend. The team manages multi-million dollar budgets, ensuring that the right message is delivered to the right consumer at the right time. Additionally, this team helps to keep our platform performing at its best by providing requests and feedback to our Product, Engineering, and Media Inventory Acquisition teams. The Media Delivery Specialist role is our entry-level position that will teach the basics of digital media campaign delivery. 

Responsibilities: 

• Oversee the targeting and media strategy of assigned advertiser accounts 
• Collaborate with AMs to engineer ideal performance solutions for each client 
• Deliver all campaigns in full and on time, meeting or exceeding client performance benchmarks 
• Maintain margin goals and ensure system is in alignment with billable numbers 
• Send daily delivery reports to Account Management team 

• Ensure all client delivery restrictions are abided by 
• Communicate specific inventory needs to the Media Acquisition team to develop publisher partnerships and increase unique reach 
• Collaborate with Product and Data Modeling teams to develop solutions that will enhance our operational efficiency and improve client performance 
• Proactively make recommendations on rate to the AM and consult on media restrictions to provide an understanding to the client on the levers that influence delivery Success Metrics 
• Delivery of campaigns against goal 

• Profit of campaigns against goal 
• Performance against client KPIs 

Requirements: 

• 1-2 years of online work experience – preferably from an ad network or agency 
• Preferred higher-educated (media, marketing or IT) or demonstrated experience in a similar business environment 
• Customer service experience 
• Knowledge of the internet and its commercial/marketing benefits 
• Strong analytical, verbal and written skills 

• Well-developed communication and presentation skills 
• Effective client management skills with a strong customer focus 
• Ability to show problem solving skills 
• Advanced computer skills (e.g. PowerPoint, Excel, Word, Outlook, and internet) 
• Ability to work with wide range of people at all decision-making levels 

• Excellent planning and organization discipline 
• Results /goal oriented 

Job Description

Epsilon Machine Learning Engineering group is looking for a Director of Data Science to lead our machine learning productization efforts.   The Machine Learning Engineering team is responsible for integrating machine learning capabilities into our Epsilon PeopleCloud suite of marketing SaaS, focusing on Epsilon People Cloud Loyalty, Messaging and Customer product solutions.  You will be part of the Machine Learning Engineering leadership team which manages a group comprised of data scientist and software developers that are researching and building automated, repeatable segmentation, predictive modeling and recommendation solutions that directly impact the marketing performance of our clients leveraging the Epsilon PeopleCloud product suite.

You have a strong machine learning and deep learning background and are passionate about transforming data into productionized ml models. You welcome the challenge of data science and are proficient in Python, Spark MLLib, Tensorflow, Keras, ML algorithms, Deep Neural Networks, big data, and cloud computing. You must be self-driven, take initiative and want to work in a collaborative, dynamic, busy, and innovative group.  You leverage your strong communication skills to represent our ML capabilities within the broader organization and provide mentorship for the team’s data scientists.  You are adept at taking complex concepts and simplify them so others can more easily understand the ML solutions we provided.

RESPONSIBILITIES

• Leverage your experience in Machine Learning to help set the strategic direction for designing automated ML capabilities in the cloud
• Design, implement, and validate productized analytic pipelines at scale using a variety of tools (AWS Sagemaker, Databricks, EMR, Spark, Python, Mllib, Git, etc.)
• Liaison with other internal groups with Epsilon to facilitate the development and adoption of our ML solutions
• Identify new analytic capabilities and compare/contrast with existing methods
• Develop an understanding of Epsilon’s current analytic capabilities, proprietary datasets, and product capabilities
• Mentor data scientists by providing feedback on algorithmic approaches and