Data Scientist

Data Scientist I

Supports statistical analyses of large datasets, the development and deployment of Machine Learning (ML), multimodal Deep Learning (DL), and Artificial Intelligence (AI) solutions that improve the relevance and value of ads across our Ad Exchange, Contextual Platform, and Attention Measurement Platform. This role focuses on applying strong analytical foundations, building and evaluating ML and DL models, leveraging general AI concepts and techniques, while also partnering closely with Engineering, Product, and Data Science teams to improve ad‑serving performance, operational decision‑making, and lead development of new AI products that best serve the business.

• Support the translation of business and product requirements into data‑driven analyses and ML solutions
• Partner with Engineering team members and senior Data Scientists to develop, test, and deploy ML and DL models
• Conduct exploratory data analysis to inform feature development and modeling approaches
• Build, run, and maintain regular pipelines to analyze production data, generate KPIs, and prepare automatic retraining of existing models
• Query, clean, and structure large datasets using SQL, Spark, and cloud data platforms
• Train, evaluate, and iterate on traditional ML models and multimodal deep learning models under guidance from senior team members
• Design and maintain Looker dashboards and other Business Intelligence (BI) tools to track Key Performance Indicators (KPI) for key stakeholders
• Develop and deploy agentic pipelines and other LLM‑powered applications, including prompt engineering, tool use, and evaluation of model outputs
• Contribute to existing Machine Learning Engineering (MLE) workflows for model training, deployment, and monitoring
• Document analyses, models, and broader learning to support knowledge sharing across the team and non‑technical audiences
• Continuously expand on statistical and AI foundations while learning new AI/ML techniques, tools, and advertising‑domain concepts

• Bachelor’s degree in a quantitative field (e.g., Statistics, CS, Math, Physics, or Economics).
• 1–2+ years in a data‑driven role such as Analytics, Data Science, or ML Engineering.
• Proficiency in Python and experience applying ML/DL methods using libraries like scikit‑learn, PyTorch, Hugging Face, or OpenCV.
• Dependable SQL skills and experience designing pipelines or DAGs using tools like Airflow or Astronomer.
• Exposure to cloud environments (AWS/GCP, Databricks, Snowflake) and large‑scale query tools like Spark or Snowpark.
• Strong grasp of A/B testing, experimental design, and statistical concepts (regression, classification, optimization).
• Experience with LLM prompting and interest in frameworks like RAG, Lang Chain, or agentic systems.
• Ability to design dashboards for diverse audiences and collaborate effectively with Product and Engineering teams.

Competitive base pay is a part of a total rewards package, which also includes benefits, an emphasis on recognition, development, and wellness. The reasonable estimated base pay range for this role is $128,000-$130,000 annually. The actual amount may be higher or lower. Individual compensation will vary based on factors including, but not limited to, relevant qualifications, work location, and labor market conditions.

The total rewards package offered also includes an employer‑matched 401(k) retirement plan, and, depending on the role, participation in a bonus, commission, or stock incentive program. Learn more about our U.S. benefits & perks package at

Gum Gum is proud to be an equal opportunity employer. We’re committed to creating a workplace where people feel respected, supported, and able to do their best work. We believe different perspectives make us stronger and lead to better outcomes—for our teams, our partners, and our business. We strive to build an environment where individuals are treated fairly, opportunities are accessible, and everyone is held to a high standard of respect and accountability.

We’re always learning and evolving as a company, and we continue to take thoughtful steps to support our people and strengthen our culture.