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Metro-based, mid-level ML role with common skillset at a well-known employer increases competition.
ML skills are transferable, but insurance domain knowledge and Databricks requirement moderately limit cross-industry fit.
Explicit 5+ years plus mandatory Databricks, ML frameworks, and monitoring increases shortlisting rigidity.
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Lead and deliver end-to-end data science projects including data preprocessing, feature engineering, model development (GLM, Generative AI, neural networks), validation, and ongoing monitoring to ensure model performance and business impact.
Collaborate with stakeholders to translate business problems into data-driven solutions and clearly communicate technical insights to both technical and non-technical audiences.
Build and mentor a high-performing data science team, promote best practices in coding, documentation, version control (GitHub), and model monitoring.
5+ years of professional experience in data science or model development roles.
Proficiency in Python and SQL and hands-on experience with Databricks (mandatory).
Experience with machine learning models including GLM, Generative AI, neural networks using frameworks like TensorFlow or PyTorch.
Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or related field; PhD is a plus.
Experienced with full model development lifecycle in large-scale, cloud-based environments especially Databricks and big data platforms (e.g., Spark, Hadoop).
Able to lead and manage teams while working cross-functionally with business stakeholders to align data science solutions to business objectives.
Strong communicator who can translate complex statistical concepts and model outputs into actionable business insights.