Responsibilities

• Define and execute data science solutions end-to-end, from problem framing through production deployment.
• Build machine learning models (classification, regression, clustering, ranking) for advertiser segmentation, propensity modeling, and recommendations.
• Apply causal inference and experimentation methods (A/B testing, difference-in-differences, propensity score matching) to measure the impact of marketing interventions.
• Analyze large-scale advertiser behavioral data to identify trends, surface growth opportunities, and support optimal decision making.
• Collaborate with colleagues across science and engineering disciplines for fast turnaround proof-of-concept prototyping at scale.
• Establish and drive data hygiene best practices to ensure coherence and integrity of data feeding into production ML/AI solutions.
• Leverage GenAI and LLM capabilities to enhance science products where applicable

Requirements

• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 2+ years of data scientist experience
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• Bachelor's degree
• Experience applying theoretical models in an applied environment

Preferred

• Experience in Python, Perl, or another scripting language
• Experience in a ML or data scientist role with a large technology company

Benefits

• comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching, paid time off, and parental leave.