Director, Data Science

About the Role

Key Responsibilities

• Create and elevate current analytics methodology, build a replicable statistical framework within the constructs of a composable analytics framework and the NEON platform.
• Model outputs and inputs, working with the Data Engineering team to assure data processes are automated and efficient.
• Work alongside product leads, business leads, data scientists, data engineers, front-end developers, and designers.
• Incorporate multiple 3rd party APIs & other datasets from different sources into custom-developed measurement and display systems.
• Demonstrated ability to extract business insights from large datasets and use them to drive business change.
• Mine, aggregate, and analyze data from databases to drive optimization and improvement.
• Evaluate external AI solutions for their modeling and predictive strength to complement NEON features and use cases.

Requirements

• At least 7 years experience in Machine Learning client analytics role.
• Experience working with client services teams and communicating technical findings directly with client technical team members.
• Domain expertise in creative analytics and creative and/or conversion rate optimization strategies.
• Deep expertise in Python (and libraries), R, SQL.
• Ability to operate in Snowflake, AWS infrastructure of S3/EC2, etc.
• Proven experience to interact in a collaborative fashion with Product Management from analytic conceptualization through to production rollout.
• Independently motivated to conceptualize and execute proactive client analysis.
• Existing skill sets in machine learning, computer vision, and product development.
• Strong communication skills and ability to collaborate with clients.
• Hold an undergraduate degree in math, statistics, computer science or other technical degree.
• Keen attention to detail and data integrity.

Nice to Have

• Experience with creative AI use cases such as creative trend projection, multivariate testing, image/video classification, custom audience segmentation, and predictive scoring.

Qualifications

• Undergraduate degree in math, statistics, computer science or other technical degree.

Benefits & Perks

• Competitive total rewards package including a discretionary bonus.
• Health insurance coverage, life and disability insurance.
• Retirement savings plans.
• Company paid holidays and unlimited paid time off (PTO).
• Mental health and wellness resources.
• Pet insurance, childcare resources, identity theft insurance.
• Fertility assistance programs, fitness reimbursement.