The Senior Data Scientist is responsible for developing and implementing ML solutions that enhance our ability to serve high-relevance and high-value advertisements - without tracking user behaviors. These solutions will focus on optimizing our ad-serving pathways, improving our operational decision making, and supporting a next-generation Ad Exchange Platform. The ideal candidate will have a strong foundation of statistical principles and ML techniques, experience working with petabyte-scale volumes of data, and a practiced understanding of deploying ML models to production applications. 

Reporting to our Data Engineering Manager, the Senior Data Scientist will be the founding member of a Machine Learning team in the media business. The person can take consulting help from machine learning teams in other divisions. This person will be able to benefit from various programs that focus on employee development and exploration of technology-related interests and passions. We are committed to fostering diversity and inclusion in our workplace and getting employees of all backgrounds and identities to join and learn from our diverse management team.

Note: GumGum currently operates in a ‘work from home’ virtual environment with sporadic opportunities for in-person business and morale events (health guidelines permitting). There will not be any requirement to go into the office on a daily basis moving forward. GumGum is only open to hiring remote candidates who are residents in the following states: AZ, CA, CO, CT, FL, GA, IA, IL, IN, KY, MA, MD, MI, NJ, NV, NY, OH, OR, PA, TN, TX, UT, VA, WA, and MN.

What You'll Achieve

• Translate business, product, and engineering requirements into ML solutions
• Conduct exploratory analyses to refine our ML roadmap and prioritization
• Query and structure large datasets for model development using Spark and SQL
• Train, experiment, and tune ML problem statements in order to find optimal solutions
• Contribute to our MLOps workflows to facilitate efficient and scalable development
• Develop KPIs in our BI platform to track and monitor model performance and the effect on other engineering and business systems
• Serve as a mentor to other Data Scientists and Engineers
• Establish a scalable ML Platform for other engineers and data scientists to use

Skills You'll Bring

• Bachelor’s degree in Statistics, Mathematics, Physics, Economics or related quantitative field (Advanced degree preferred)
• 2+ years deploying ML models to production applications
• 5+ years in a data-driven role transforming data into business value
• 5+ years collaborating with Engineering and Product
• Nice to have: 1+ year contributing to MLOps workflows
• NIce to have: experience working within ad-tech
• Strong with SQL - writes efficient and well-organized statements
• Proficient in Python, Scala, or Java and related ML libraries
• Production experience using some MLOps tools - Feature Store, Model Registry, MLflow, Kubeflow, Docker, git, notebooks
• Experience with big data technologies - Spark or similar frameworks
• Familiar within cloud data environments - AWS, GCP, Databricks, Snowflake, Looker, PowerBI, Tableau
• End-to-end ownership - likes working on all phases of an ML solution; from ideation and discovery to deployment and monitoring
• Desire and dedication towards understanding complex systems - the advertising domain has A LOT of data and many decision points
• Enjoys and excels at communicating in both business and technical conversations
• Likes skill-sharing and working with others - there will be a lot of opportunities to mentor and learn new technologies

What We Offer

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