The Data Scientist II is responsible for delivering 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 large-scale volumes of data, and a practiced understanding of deploying ML models to production applications. This position will report to the Senior Manager, Data Engineering as part of a Data Science team within the Media division. 

GumGum engineering is a collaborative and supportive work environment. This individual will have the opportunity to thrive through a range of programs designed to support professional growth and the pursuit of technology-related interests and passions. We are dedicated to creating an inclusive and diverse work environment, where individuals of all backgrounds and identities are welcome to join and gain valuable insights from our diverse leadership team. Additionally, this individual is welcome to seek guidance and support from machine learning teams in other divisions.

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
• 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
• Contribute to 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 of experience in quantitative analysis & data science or a related field
• 1+ year experience deploying ML models to production applications
• Collaborating with Engineering and Product
• Nice to have: MLOps experience
• NIce to have: Adtech experience
• Applied statistical techniques, such as inferential methods, causal methods, A/B testing, or statistical modeling techniques
• Strong with SQL - writes efficient and well-organized statements
• Experience with Python, Scala, or Java + related ML libraries
• Familiar with big data technologies - Spark or similar frameworks
• Familiar with 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
• Likes skill-sharing and working with others - there will be a lot of opportunities to mentor and learn new technologies
• Excels at communicating in both business and technical conversations
• Desire and dedication towards understanding complex systems - the advertising domain has A LOT of data and many decision points
• Understands how to transform data into business value
• Encourages a diverse range of perspectives by generating new ideas and openly sharing them

What We Offer

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 ($143,000 - $161,000) 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.