Principal Applied Scientist

The Applied Scientist develops causal machine learning models and rigorous experiments to optimize borrower acquisition across marketing channels. The role requires a master’s degree and experience with Python, statistical modeling, machine learning, causal inference, and experimental design.

About the job

Responsibilities

Analyze historical model and campaign performance to identify opportunities to improve model effectiveness and marketing outcomes.
Develop and evaluate machine learning models, including new features and model architectures, for prospect selection and emerging marketing use cases.
Design statistically rigorous experiments and model evaluations to measure causal impact and optimize campaign outcomes.
Work with complex datasets and build reusable data pipelines, metrics, and analytical approaches.
Partner with Machine Learning, Growth, and Marketing Platform Engineering teams to translate business problems into research agendas and production-ready solutions.
Expand machine learning capabilities into lifecycle, email, digital, and other marketing channels.

Requirements

Master’s degree in Mathematics, Statistics, Economics, Operations Research, or a related field.
Experience applying statistical and machine learning methods to modeling or data science problems.
Python experience for data analysis, data preparation, and machine learning model development.
Experience with causal inference and experimental design.

Nice-to-haves

PhD in Mathematics, Statistics, Economics, Operations Research, or a related field.
Knowledge of causal machine learning methods and modeling approaches.
Ability to translate broad business problems into research questions, analyses, and modeling approaches.
Experience across exploratory data analysis, machine learning research, experimentation, and production model development and scaling.
Ability to interpret complex experimental or modeling results and provide actionable recommendations.
Experience applying machine learning to marketing, customer acquisition, lifecycle, or growth use cases.

Compensation and Benefits

United States anticipated base salary: $141,500–$196,000 USD.
Canada anticipated base salary: $130,900–$160,000 CAD.
Target bonuses, equity compensation, and benefits including medical, dental, vision, retirement plans, employee stock purchase options, paid leave, family-centered benefits, employee assistance resources, and wellness support.

Skills

Python, Machine Learning, Causal Inference, Experimental Design, Statistical Modeling, Causal Machine Learning, Data Analysis, Data Pipelines, Exploratory Data Analysis, Marketing Analytics