Data Scientist / Engineer

Job description

We are a stealth company revolutionizing the marketing landscape with our AI-powered platform. Our team has pioneered AI-based marketing systems at some of the most iconic companies in the world including Expedia, Amazon, Snapchat, and BCG - to transform how businesses direct their marketing spend to drive unprecedented growth and efficiency.

Our founders bring a wealth of experience and expertise from their tenures at industry giants such as Meta, Expedia, Snapchat, and YCombinator. We are proud to be backed by Silicon Valley's top venture capital funds and angel investors, who share our vision and commitment to innovation. Together, we are on a mission to redefine marketing with AI, and we invite you to join us on this exciting journey.

We are looking for a Data Scientist to join our growing company. In this role, you will leverage the latest in deep learning, reinforcement learning and transformers to build cutting-edge marketing optimization models (i.e. bidding, budget, audience and creative optimization). This is a hands-on, technical role where you will have the opportunity to develop and deploy scalable models and push the limits of what is scientifically possible.

Key Responsibilities:

Paid Media Optimization Modeling:

Develop and refine cutting-edge machine learning models to optimize marketing strategies across various media channels (e.g., search, display, social).

Build models to optimize bidding, budget allocation and creative performance, ensuring maximum return on ad spend (ROAS).

Design and implement on-platform A/B tests to measure efficacy of marketing strategies

Insights and Reporting:

Build large data / ETL pipelines to retrieve large sets of marketing data from various paid media sources (Google Ads, Facebook, Ads, DSPs, etc)

Build actionable reports and insights for marketing teams to drive campaign performance and efficiency.

Model Productionization

Translate model prototypes into a production data science pipeline that is reliable and resilient and can support product SLAs

Collaborate with product engineers to deliver data science model output

Qualifications:

Education: Master's degree or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or a related field.

Experience: 3+ years of hands-on experience in data science roles

Expertise in statistical modeling techniques, machine learning algorithms (e.g., random forests, gradient boosting, neural networks), and optimization methods.

Proficiency in programming languages such as Python or R for data analysis, model building, and machine learning.

Strong skills in big data wrangling and manipulation using Spark, SQL and/or other experience working with large-scale data sets.

Experience with cloud platforms (AWS, Google Cloud, or Azure) and tools for model deployment.

Excellent communication and presentation skills, with the ability to convey complex analytical concepts to non-technical audiences.

Strong collaboration skills and the ability to work closely with cross-functional teams, including marketing, data engineering, and business intelligence.

Results-driven with a focus on driving business impact through data science.

Preferred Qualifications:

Experience in building and deploying media optimization models (bidding, budget allocation, creative performance) in a production environment.

Experience in cutting-edge deep learning models like graph neural networks, causal machine learning and reinforcement learning.

Experience with time-series forecasting and simulation for marketing scenario planning.

• Familiarity with digital marketing KPIs and performance metrics such as CTR, CPA, ROAS, and LTV.