We’re looking for a Data Scientist to join our growing team and build ML-driven models that power how we measure ad performance across reach, frequency, lift, and attribution. If you’re passionate about data, love solving complex problems, and thrive in a collaborative environment, this role is for you.

What You’ll Do

• Build statistical and ML models to reduce bias and analyze large-scale experiments.
• Translate research into production workflows using PySpark and SQL.
• Collaborate with engineering to develop scalable, cloud-based measurement pipelines.
• Design and optimize data models that measure ad performance across massive, diverse datasets.
• Troubleshoot models and validate underlying assumptions.
• Work with internal and external stakeholders to deliver insights and build new product features.

What You Bring

• Master’s (3–5 yrs exp) or PhD (0–2 yrs) in a quantitative field (e.g., Statistics, CS, Math).
• Strong foundation in probability, statistics, and machine learning.
• Proficiency in Python (Pandas, NumPy, scikit-learn) and SQL.
• Experience with PySpark and working in cloud environments (AWS/GCP).
• Solid software skills: Git, OOP, and command-line tools (e.g., bash).
• Curious, collaborative, and comfortable in a fast-paced environment.
• Excellent communication skills—you can explain complex ideas to technical and non-technical audiences.

Bonus Points

• Experience with ad-tech or digital advertising measurement.
• Familiarity with randomized control trials, lift/attribution models.
• Experience contributing to a mature, Python-centric codebase.

Why Join Us?

• Tackle high-impact problems at the intersection of data science and ad-tech.
• Work on a collaborative, smart, and mission-driven team.
• Flexible remote work, modern tech stack, and strong learning culture.