Senior Staff Data Scientist

Overview In this role you will lead the data science and ML technical strategy at IAA, architecting scalable ML systems and AI applications with a strong business focus. You will drive cross-functional collaboration to deploy data-driven solutions across customer behavior, vehicle listings, and other core domains. You will shape technical direction, mentor engineers, and deliver measurable growth and operational efficiency through enterprise-scale AI. The opportunity centers on building advanced models, AI agentic workflows, and end-to-end platforms that empower rapid, data-informed decision making. You will have a visible impact on how IAA leverages ML to transform processes and outcomes at scale. Compensation / Benefitsmedical, dental, vision, and basic life insurances 401k with 100% match up to 4%15 days of PTO per year Responsibilities Define and drive the data science and ML roadmap for the organization Architect and build end-to-end ML systems from data strategy to deployment and monitoring at scale Develop and productionize advanced supervised, unsupervised, and deep learning models including NLP and computer vision Build AI agentic applications and LLM-powered solutions to automate workflows Perform feature engineering, data validation, and quality assurance on large datasets Collaborate with data engineering, ML platform, and software engineering teams to ensure scalable and reliable models Translate cross-functional business problems into technical strategies and communicate with executives Mentor and elevate staff and senior data scientists, establishing standards and direction Key requirements 8+ years of experience building and deploying production ML systems (supervised, unsupervised, deep learning)Advanced proficiency in Python and SQL, with scikit-learn, PyTorch or Tensor Flow, pandas, Num PyHands-on NLP and computer vision experience Experience building AI agentic applications with Lang Chain, Lang Graph, or similar, including LLM integration Full ML lifecycle experience: feature engineering, training, tuning, evaluation, deployment, monitoring Strong foundation in statistics and core ML algorithms Experience architecting ML solutions on large-scale datasets using Spark, Dask and cloud platforms (AWS, Azure, or GCP)Ability to set technical direction, influence roadmaps, and communicate with executive stakeholders Track record mentoring senior data scientistscross-functional collaborationclear technical communicationmentorship and leadership PythonSQLscikit-learn