Gradient AI Offices

Manage the post-sale client lifecycle for health insurance customers, including implementation, workflow design, dashboard analysis, ROI measurement, project management, and relationship building. Serve as the primary client contact while coordinating with Sales, Product, Data Science, and Engineering. Ensure clients successfully adopt and maximize the value of predictive analytics solutions through strong communication, documentation, and ongoing engagement.

Build and maintain automated data quality testing for customer data pipelines. Responsibilities include developing dbt, Soda, and SQL checks; validating schemas, loads, sequencing, and downstream reconciliations; detecting anomalies; managing severity levels and customer overrides; reporting quality metrics; and partnering with engineering teams to embed testing into new pipelines. The role requires strong backend testing, SQL, Python, Airflow, and Databricks experience, along with excellent debugging and communication skills.

Lead complex modeling projects combining deep learning, LLMs, and traditional techniques. Prototype, deploy, and monitor production models, mentor data scientists, collaborate with engineering/product, and translate results into business impact for insurance customers.