Senior Manager - Data Science

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Requirements:

• 6+ years working in consumer marketing analytics with at least 5 years in a management role and experience managing/developing data scientists.
• Proven leader that is used to setting quarterly roadmaps for teams based off business needs, providing technical mentorship and leadership to a high performing group.
• Experience with developing and maintaining MMM and/or MTA solutions.
• Excellent analytical and critical thinking skills, and superior presentation and content dissemination skills.
• Player coach who can read and write SQL, Python and/or R.
• Experience with a big data environment / IDE, such as Databricks and/or Snowflake.
• Experience with marketing data architectures, such as CDPs (customer data platforms), digital log files (e.g. Adobe Analytics), and stimulus data (e.g. Google Campaign 360, aggregated agency data).
• Able to navigate a highly matrixed organization, remove barriers to execution, and influence others with high EQ.
• Bachelor's degree in a related field, such as mathematics, economics, data science, or engineering; a Master's degree or MBA is preferred.

Responsibilities:

• Provide thought leadership and strategic thinking to translate business problems into analytical frameworks, and independently recommends actions and provide business insights.
• Lead the development and implementation of advanced analytics and machine learning, including delivery roadmap, prioritization, methodologies, development of models and MLOps.
• Manage priorities and allocates resources as well as communicate business performance and project progress to management and business partners.
• Collaborate and partner with the Data Platform and Enterprise Architecture teams to ensure data architectures, models and pipelines are designed and built to enable, monitor, and sustain data science and machine learning.
• Develop, implement and maintain analytics enterprise analytics roadmap together with team leadership and cross functional peers.
• Help grow the sophistication of the team’s analyses with LTV models, acquisition cost optimization, ROAS optimization, media mix modeling and Multi-touch Attribution.