Senior Data Science Leader: Production ML & Optimization (Remote)

Gainor Staffing; New York (NY); Hybrid; USD 180,000 - 200,000; Full time

Benefits offered by this job

Remote-friendly

Hybrid option NYC preferred

Annual performance bonus

Unlimited PTO

401k with match

Medical benefits

Parental leave

Job summary

Gainor Staffing is assisting a premier data-driven media firm in finding a Director of Data Science. This senior IC role demands hands-on leadership with production-grade Python, ML, and optimization work to guide media planning and strategy.

You’ll translate complex business problems into scalable solutions, mentor scientists, and collaborate with engineering and strategy teams to embed models into the tech ecosystem.

Qualifications

• 7+ years of quantitative modeling, statistics, and production-grade Python development.
• 5+ years building and deploying data science software.
• Master’s or PhD in a STEM discipline preferred.
• Fluency in SQL and familiarity with cloud technologies, Git, and modern data pipelines.
• Excellent communication and stakeholder-facing skills.

Responsibilities

• Build production ML models and optimization tools for media planning.
• Translate business challenges into scalable quantitative solutions.
• Mentor data scientists and guide production-level systems.
• Work with engineering, media strategy, and channel teams to integrate models.
• Contribute to a culture that values rigor, creativity, and collaboration.

Skills

Production-grade Python

Quantitative modeling

Statistics

SQL proficiency

Cloud technologies

Stakeholder communication

Education

Master’s or PhD in a STEM discipline

Tools

Git

Cloud platforms (AWS/GCP)

Data pipelines

Job description

Gainor Staffing is assisting a premier data-driven media firm in finding a Director of Data Science. This senior IC role demands hands-on leadership with production-grade Python, ML, and optimization work to guide media planning and strategy.

You’ll translate complex business problems into scalable solutions, mentor scientists, and collaborate with engineering and strategy teams to embed models into the tech ecosystem.