Ensure AI models remain accurate and continuously improved to meet business and compliance requirements. Leverage data science methods to drive insights and improve performance for informed decision-making. Responsibilities include fine-tuning AI models, monitoring outputs, and developing strategies for handling bias and compliance issues.
At Thumbtack, Data Scientists combine rigorous thinking, technical expertise, and business context to accelerate smarter decisions and better products. As a Staff Marketing Data Scientist, you will serve as one of the most senior members of the team, setting the bar for technical innovation and strategic impact. Your mission will be to advance our channel measurement capabilities and to design scalable methodologies, frameworks, and tools.
This position is central to delivering on our key activities of customer engagement and distribution through the creation of AI driven marketing optimization processes. This role will focus on increasing the efficacy of our Direct Mail process by delivering a new suite of ML models ranging from propensity models to LTV models. This role will be crucial in reducing our reliance on affiliate partners through expanding our customer base in non-affiliate channels.
As a Staff Data Scientist, you will identify and drive new strategic opportunities through advanced machine learning models and analytics by designing data capture systems, operational processes, experimentation frameworks, and feedback mechanisms. You'll lead end-to-end model development and deployment processes, leveraging classical ML methods and LLM based methods based on agentic AI and collaborating across teams.
Design end-to-end AI architectures, including data pipelines, model development, deployment, monitoring, and integration into enterprise systems. Leverage modern AI/ML frameworks and platforms. Ensure solutions follow best practices for scalability, reliability, and responsible AI. Partner with client stakeholders to understand business challenges and translate them into AI-driven solutions. Provide technical leadership in workshops and architecture design sessions.
Provide the necessary machine learning/data science expertise, and collaborate with data analysts and data engineers, so that the Analytics Solutions team can deploy analytical approaches and tools to support business stakeholders. Leverage the organization’s data assets to develop, maintain, and support the implementation of predictive models that improve business performance.
The USRM Claims Data Science team is hiring an Analyst II, Data Science, as part of a broader expansion of our team. This role will focus on supporting the Auto Physical Damage claims organization. As an Analyst II, Data Science, you will collaborate with business partners to develop predictive models that enable dynamic software systems and data-driven strategic decision-making.
Large‑scale language models are evolving into powerful engines of scientific discovery. As a STEM specialist, you will challenge advanced language models on topics like thermodynamics, mechanics, calculus, statistics, materials science, electronics, algorithm design, and quantitative modeling. You will converse with the model on real-world STEM problem-solving scenarios and theoretical technical questions, verify factual accuracy and logical soundness, and suggest improvements.
This role involves building a cohesive data organization that fosters collaboration and drives innovation across the entire company. The Senior Director of Data Engineering will drive the transformation of multiple teams and forge partnerships between the data organization and product engineering, while also enhancing the company’s competitive edge.
We are seeking an experienced and strategic Director of Analytics reporting directly to the VP of Analytics, Data Science & Clinical Intelligence. This role will be responsible for leading a critical function within our organization and serving as the primary strategic data partner for our Growth (Sales) and CX (client success, client delivery, marketing) functions. This role will lead a high-performing team of data scientists.