Job Summary

Gallagher Center of Excellence is seeking a Data Scientist to join the analytics vertical. In this role, you will be part of a data science team focused on preparing and analyzing data, contributing to model development, and helping deploy analytic solutions. This position is ideal for candidates with basic to intermediate knowledge of statistical methods, machine learning concepts, and programming who are ready to apply and expand their skills in a supportive technical environment.

Responsibilities

- Clean and preprocess raw datasets to address missing values, outliers, and inconsistencies, ensuring a solid foundation for analysis.
- Perform exploratory data analysis (EDA) to uncover trends, distributions, and anomalies using summary statistics and visualizations.
- Assist in feature engineering by creating, transforming, and encoding variables to improve model inputs and capture domain insights.
- Build and validate baseline predictive models (e.g., linear regression, logistic regression, decision trees) to establish performance benchmarks.
- Calculate and interpret evaluation metrics (RMSE, accuracy, precision, recall) to compare model outputs and guide further tuning.
- Develop clear, concise data visualizations and dashboards (using Matplotlib, Seaborn, or Tableau) to communicate findings to internal teams.
- Maintain reproducible analysis pipelines with version control (Git), modular code structure, and automated scripts.
- Monitor and troubleshoot data ingestion and ETL processes to ensure timely,



high-quality data availability for analytics tasks.
- Document data sources, transformation steps, model assumptions, and validation results to support transparency and knowledge sharing.
- Stay up to date with emerging data science tools and techniques, experimenting in sandbox environments and sharing learnings with peers.

Qualifications

- Preferred Degree: Bachelor s / Master s Degree in Statistics / Applied Math/Stats
- Experience: 2- 4 years in data science, analytics, or quantitative modeling roles, contributing to data preparation, exploratory analysis, and basic machine-learning model development; familiarity with insurance brokerage or related financial services is a plus.
- Basic statistical concepts and introductory machine-learning methods (linear regression, logistic regression, decision trees).
- Proficiency in Python and SQL for data manipulation, analysis, and easy model building.
- Hands-on experience with data cleansing and preprocessing using libraries such as pandas or NumPy.
- Working knowledge of version control (Git) and best practices for writing reproducible, well-documented code.
- Solid analytical mindset, attention to detail, and clear written and verbal communication skills for summarizing findings

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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