Senior, Data Scientist

About the Role

Key Responsibilities

• Lead clean-room data science initiatives with Meta and Pinterest, managing workflows such as audience joins, attribution measurement, and cross-channel measurements.
• Collaborate with cross-functional teams to define scalable schema, governance protocols, and privacy-safe data-sharing pipelines supporting campaign measurement and audience activation.
• Design and implement advanced Generative AI solutions for social listening, building systems that analyze comment data for sentiment, intent, and brand affinity signals.
• Transform unstructured social content into structured insights to deliver actionable recommendations to campaign managers and advertisers.
• Integrate third-party data sources to enhance targeting accuracy and segmentation depth for personalization and high-value audience activation.
• Develop scalable audience automation frameworks by integrating clean-room capabilities with internal and external media platforms.
• Support go-to-market strategies by creating training materials, case studies, and data-driven narratives for sales enablement.
• Develop innovative measurement solutions in Data Clean Rooms using advanced ML algorithms and statistical techniques.
• Participate in analytics consultation projects, advising on experimental design, success metrics, and testing requirements for new products and partnerships.
• Manage end-to-end project execution from planning to deployment, communicating effectively with stakeholders.
• Conduct statistical power analyses and analyze experiment results using advanced statistical techniques.

Requirements

• Proven experience as a Senior Data Scientist with a focus on marketing analytics, preferably in retail or membership-based environments.
• Experience with statistical analysis, experimental design, regression modeling, and machine learning using tools such as Python, R, Spark SQL, and MLlib.
• Strong knowledge of ad-tech and mar-tech industry, including econometric modeling, digital attribution, A/B testing, and predictive modeling.
• Excellent communication skills to translate complex findings into actionable insights for non-technical stakeholders.
• Ability to work with ambiguity and thrive in a rapidly changing environment.
• Familiarity with retail and membership concepts is a plus.
• AI/ML engineering experience in building scalable media measurement and targeting solutions is a big plus.

Nice to Have

• Data science, machine learning, optimization models, or related master's degree.
• Successful completion of assessments in Python, Spark, Scala, or R.
• Experience with open source frameworks like scikit-learn, TensorFlow, or Torch.
• Knowledge of creating inclusive digital experiences and implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards.
• Experience with digital accessibility and assistive technologies.

Qualifications

• Option 1: Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field plus 3 years' experience in analytics.
• Option 2: Master's degree in relevant fields plus 1 year of experience.
• Option 3: 5 years' experience in analytics or related field.

Benefits & Perks

• Competitive pay with incentive awards for performance.
• Health benefits including medical, vision, and dental coverage.
• Financial benefits such as 401(k), stock purchase plan, and company-paid life insurance.
• Paid time off including PTO, parental leave, family care leave, bereavement, jury duty, and voting.
• Other benefits like short-term and long-term disability, company discounts, military leave pay, and expense reimbursements.
• Live Better U education benefit program covering tuition, books, and fees for various educational levels.