Gallagher · 3 days ago

Manager, Data Science

Chicago, IL

Full-time

Onsite

Senior Level

7+ years exp

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ConsultingFinancial Services

Actively Hiring

Hiring Manager

Nick Perna

Insider Connection @Gallagher

Discover valuable connections within the company who might provide insights and potential referrals, giving your job application an inside edge.

Responsibilities

Develop, analyze, and model operational, economic, management, accounting, and other organizational data.

Apply statistical, mathematical, predictive modeling, and business analysis skills to manage and manipulate complex high-volume data.

Manage and provide oversight for a team of data science professionals.

Apply industry knowledge to a data science context, building real-world use cases.

Utilize Generative AI on a wide range of tasks.

Present Data Science methods and outcomes to high-level leaders and large audiences.

Qualification

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Quantitative Field DegreeStatistical ModelingMachine LearningData AcquisitionModel BuildingDeploymentMonitoringInsurance Industry KnowledgeMarket-Facing Functions KnowledgeCloud Tools (Azure)Distributed Data/Computing Tools SparkDistributed Data/Computing Tools SnowflakeDistributed Data/Computing Tools DatabricksDistributed Data/Computing Tools OpenAIDistributed Data/Computing Tools Hugging FaceDevOps

Required

Degree in a quantitative field, such as data science, statistics, mathematics, computer science, finance, or economics.

7 years of experience, including using statistical modeling and/or machine learning techniques to build models that have driven company decision-making, and/or experience in the insurance, insurance brokerage, or consulting industry.

Master's or PhD preferred in a quantitative field.

Experience working through the full life cycle of data acquisition, model building, deployment, and monitoring in a production environment.

Experience with market-facing functions of the insurance industry, such as underwriting, sales, claims, or consulting.

Experience with cloud tools and structures, preferably Azure, as well as distributed data/computing tools like Spark, Snowflake, Databricks, OpenAI, Hugging Face and DevOps.