Description
Senior Applied Scientist
Thumbtack, Inc. (San Francisco, CA) to be responsible for demonstrating deep expertise in developing and deploying advanced machine learning (“ML”) models, including frontier artificial intelligence (“AI”) and large language models (“LLM”) models, to analyze various aspects of user and pro behavior, platform interactions and payment data to proactively address potential threats; initiating and driving applied science initiatives to completion with a focus on improving the trust and safety of the platform, including identifying opportunities to leverage machine learning to enhance spam and fraud detection, policy enforcement, and overall platform security; architecting and deploying artificial intelligence and machine learning systems and algorithms to production; designing and executing experiments to evaluate the effectiveness of new models and strategies for improving trust and safety metrics such as reducing exposure to spam, detecting abuse and improving lead quality; analyzing a wide variety of data: structured and unstructured, observational and experimental; collaborating with engineering, product, and operations teams to define problems, develop solutions, and ensure the successful implementation and monitoring of machine learning models for Trust and Safety; and contributing to improving the overall performance of Trust & Safety models by exploring new features, algorithms, and data sources.
Must have Master’s degree in Computer Science, Data Science, Machine Learning, Applied Math, Statistics, Robotics, AI, Engineering or a directly related field. Must have three (3) years of work experience in the position offered or related. Must know (through academic training or work experience) data analyses using mathematical modeling; conceptualize advanced model design, advanced study protocols and statistical analysis plans; preparing "final quality" analysis plans and study protocols; conceptualize model design; design and deployment of advanced, discrete event simulation models for forecasting to support executive decision-making on market access, quantifying risks and opportunities; performing exploratory data analysis (EDA) on Real-World Evidence (RWE) datasets; applying advanced statistical methodologies to quantify data and yield features for predictive models; develop Marketing Mix Models (MMM) to quantify the incremental return on investment (ROI) across all marketing and sales channels; and implement and interpret complete statistical analyses. $174,512 – $180,000/yr.
May work from home anywhere in the continental U.S.
Actual offered salaries will vary and be based on various factors, such as calibrated joblevel, qualifications, skills, competencies and proficiency for the role. EEO.
To apply (Ref#415022), visit https://tinyurl.com/hwvjrve8
