Applied Researcher, Data Science

Dstillery is the leading AI ad targeting company. We empower brands and agencies to target their best prospects for high-performing programmatic advertising campaigns. Backed by our award-winning Data Science, Dstillery has earned 24 patents (and counting) for the AI technology that powers our precise, scalable audiences. Our newest technology, ID-free ® , is patented, privacy-safe behavioral targeting that reaches 100% of ad impressions and can be used with any Dstillery product. Our premier user segment product, Custom AI Audiences, is a just-for-your-brand targeting solution that refreshes hundreds of millions of users every 24 hours to deliver the best performance. About the team: Data Science is at the core of our offerings at Dstillery, and as a result all members of our Data Science team have the opportunity to make an impact on our company and the industry. The Data Science Research team leads the creation and development of new products to meet the ever changing needs of the digital advertising industry. We focus on building high performing products for our clients with integrity and transparency, and we have a commitment to the development of privacy friendly solutions. As a Applied Researcher on the Data Science team you will play a critical role in bringing new products to market. Role: Prototype innovative ideas, conduct experiments, and iterate quickly to develop data-driven solutions for complex business challenges Independently work on end-to-end research projects while actively collaborating with a team of data scientists Present and promote results to internal stakeholders and external clients and partners. Support and improve existing data science products Analyze large, complex, and noisy datasets to extract actionable insights and support data-driven decision-making Design, implement and evaluate machine learning and statistical methods to perform exploratory data analysis, data storytelling and product development Design and execute A/B tests and experiments to optimize product performance and maximize revenue growth Pursue patents where applicable Contribute to thought leadership in the community with presentations and publications Qualifications: Independent research experience is mandatory. A Ph.D. in a quantitative field (e.g. machine learning, statistics, physical science, or quantitative social science) is preferred, or a M.S. in Machine Learning or statistics with at least 3 years of independent research. Experience using real data to solve real problems. Expertise in statistical modeling, machine learning, and fluency in the related technical tools. Interest in applying machine learning to large datasets to solve business problems. Knowledge of current large language models and generative AI tools and an interest in applying them to data products. Excellent oral and written communication skills; comfort in a client-facing role. A track record in contributing to publications and/or presentations in a quantitative field. Intermediate programming skills. You should be ready to learn and work with Python, Google Cloud Platform, Scikit-learn, TensorFlow, PyTorch, Spark, BigQuery and SQL