Sr. Principal Machine Learning Revenue Architect

FreeWheel, a Comcast company, provides comprehensive ad platforms for publishers, advertisers, and media buyers. Powered by premium video content, robust data, and advanced technology, we’re making it easier for buyers and sellers to transact across all screens, data types, and sales channels. As a global company, we have offices in nine countries and can insert advertisements around the world.

Job Summary

The Machine Learning Revenue (MLR) Architect is a senior leadership role responsible for leading and coordinating the strategic development of MLR solutions. This position requires a blend of business understanding, critical thinking skills along with expertise in Machine Learning (ML) methodologies, business process and systems architecture design. Key duties include designing how algorithms embed within broader systems, leading engineers, data scientists and analysts, and collaborating with business stakeholders to ensure efforts drive economic growth.

Job Description

• Opportunity Definition Work with business and operational teams to understand the problem, the operational and system constraints, the available data, and decision points. Communicate this to the team to ensure team members have a clear understanding of the problem. Define how opportunities fit within the long-term evolution of the systems.

• Define Project KPIs and Analytics Strategies : Based on the problem and the

• available data, determine how we can measure success and monitor system

• outcomes/dynamics.

• Solutions design: Define and drive the evolution of the solution, identifying points of high leverage, and phases/evolution of the system. Determine whether and how 3rd party capabilities can be integrated into the solution. Solutions may include changes to data, operational processes, and software systems.

• Project stewardship: Evolve plans and direction as we iteratively gather feedback and learn about solution effectiveness. Identify and resolve roadblocks, miscommunication, and misunderstanding, and, as needed, adapt plans to meet target timelines.

• Stakeholder management: Collaborate with cross-functional leaders to identify opportunities, communicate and evaluate solutions, and gather feedback.

• Team leadership: Mentor of data scientists and analysts, fostering a collaborative and high-performing environment. Passionate about solving problems, and inspires similar spirit in team members.

• Technical direction: Provide technical guidance, set standards, and ensure the team uses appropriate tools and methodologies.

• Innovation: Stay current with emerging trends in data science, AI, and big data

• technologies to drive innovation and maintain a competitive advantage.

• Consistent exercise of independent judgment and discretion in matters of significance.

• Regular, consistent and punctual attendance. Must be able to work nights and weekends, variable schedule(s) as necessary.

• Other duties and responsibilities as assigned.

Required skills and qualifications

• Education: A Master's or PhD in a quantitative field such as Management Science, Computational Economics, Statistics, or Computer Science, or equivalent industry experience.

• Experience: Extensive experience in Advertising Technology, with a proven track record of delivering business results.

• Business acumen: Strong understanding of how math can be leveraged to solve business problems and drive growth. Strong understanding of digital advertising

• ecosystem and technologies. Exceptional problem-solving and critical thinking skills.

• Technical proficiency: Strong expertise in statistical analysis, machine learning, data mining, and data visualization.

• Programming: Proficiency in languages like Python or R, and experience integrating solution into the enterprise infrastructure

• Big data: Experience with big data technologies such as Hadoop and Spark.

• Leadership: Proven experience in leading and managing teams of technical professionals

• Communication: Excellent communication and presentation skills to translate complex data into actionable business strategies for various audiences.

Employees at all levels are expected to:

• Understand our Operating Principles; make them the guidelines for how you do your job.
• Own the customer experience think and act in ways that put our customers first, give them seamless digital options at every touchpoint, and make them promoters of our products and services.
• Know your stuff be enthusiastic learners, users and advocates of our game-changing technology, products and services, especially our digital tools and experiences.<