Data Scientist I

GumGum • Santa Monica, CA

2d • $128,000 - $130,000 • Hybrid

About The Position

GumGum is the contextual-first technology leader transforming digital advertising with AI-powered, non-invasive data and media solutions. We champion effective advertising that uplifts and respects consumers. Our proprietary Contextual, Attention, and Creative solutions create the perfect match between a brand and a consumer in the right moment and mindset. Founded in 2008, GumGum is headquartered in Santa Monica, California, and operates in 19+ markets. To be a part of this next phase of digital advertising that prioritizes data privacy, please visit www.gumgum.com/careers The Data Scientist I supports the development and deployment of Machine Learning (ML), statistical analysis, 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 models, and partnering closely with the Engineering, Product, and Data Science team to improve ad-serving performance and operational decision-making. The ideal candidate is curious, data-driven, and eager to develop a strong understanding of the advertising domain and the systems that power large-scale decision-making. You will work with large datasets, contribute to production ML systems, and gain hands-on experience across the ML lifecycle — from exploration to monitoring. Note: GumGum fosters a flexible work environment, offering GumGummers the ability to work either in-office or remotely/from home. For this position, in-person/office collaboration is required 2 days per week , supporting a balanced approach to flexibility and team engagement.

Requirements

• Bachelor’s degree in Statistics, Mathematics, Physics, Economics, Computer Science or a related quantitative or technical field
• 1–2+ years in a data-driven role (Analytics, Data Science, or similar) -- WE ARE OPEN TO RECENT GRADS WITH INTERNSHIP EXPERIENCE
• Experience applying ML and statistical methods to real-world datasets
• Experience collaborating with Engineering and/or Product teams

Nice To Haves

• exposure to production ML systems or MLOps tools (MLFlow, Weights & Biases, etc,)
• familiarity with advertising, marketplaces, or large-scale decision systems

Responsibilities

• 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 models
• Conduct exploratory data analysis to inform feature development and modeling approaches
• Query, clean, and structure large datasets using SQL , Spark , and cloud data platforms
• Train, evaluate, and iterate on ML models under guidance from senior team members
• Contribute to existing MLOps workflows for model training, deployment, and monitoring
• Help define and track Key Performance Indicators in our Business Intelligence tools to measure model performance and downstream impact
• Document analyses, models, and learnings to support knowledge sharing across the team
• Continuously learn new ML techniques, tools, and advertising-domain concepts

Benefits

• At GumGum, 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 from $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.
• Your recruiter can share more specifics during the hiring process.
• Learn more about our U.S. benefits & perks package at gumgum.com/benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Number of Employees: 251-500 employees