Applied Scientist

We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help optimize marketing channels, via observational testing frameworks, counterfactual modeling, and lifetime value estimation. As a key member of our diverse organization, you'll have the rare and rewarding opportunity to work with datasets of unique magnitude, richness, and dedication to privacy that will frequently require novel approaches. You'll work alongside partners across Business, Marketing, Product, Finance, and Engineering daily to deliver material customer and business value.

As an Applied Scientist, you will have the responsibility of pushing the boundaries of how Causal Inference and AIML can be leveraged to better serve our customers. You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference solutions, that directly impact our products and provide a granular understanding of key marketing effectiveness. You will also be instrumental in defining the technical vision, strategy, and execution roadmap for our AIML initiatives, ensuring that we deliver high-quality, scalable, and impactful models that solve complex customer acquisition and engagement challenges. You will also be a key driver in fostering a vibrant culture of innovation, continuous learning, and collaborative problem-solving.

Master's degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field

3+ years of experience as an Applied Scientist, Machine Learning, or Data Scientist role

Familiarity with a brand range of quasi-experimental Causal Inference techniques such as diff-in-diff, synthetic control method, panel analysis, regression discontinuity design, interrupted time series, and propensity score matching

Hands-on experience building Marketing Mix models and validation through Matched Market testing

Solid understanding of AIML technologies including Generative AI

Proven track record of successfully delivering complex projects from start to finish

Proficiency in programming languages such as Python, R, SQL, Java, or C++

Experience with cloud platforms, Spark, Docker, and MLOps tools and best practices

Excellent communication, collaboration, and presentation skills with meticulous attention to detail

PhD in related field

Hands-on experience leveraging Generative AI to improve productivity and generate new insights

Curious business attitude with an ability to condense complex concepts and models into clear and concise takeaways that drive action