Roles and Responsibilities

• Lead large-scale analyses of new or existing data sources to identify relationships, anomalies, or opportunities for strategic insights.
• Establish links across multiple data sources and uncover non-obvious patterns or correlations.
• Develop, evaluate, and deploy machine learning models (e.g., regression, decision trees, clustering, SVMs, neural networks) including model scoring code using modern ML tools.
• Build and maintain advanced dashboards using tools such as Tableau, Alteryx, or other BI platforms to support ongoing product and analytics initiatives.
• Perform complex data transformations and enrichments using Python, SQL, and other ETL languages.
• Clearly document all analytical and technical work and actively mentor and train colleagues across BI and data teams.
• Present analytical findings to technical and non-technical stakeholders, including executive leadership, in a clear and concise manner.
• Work with architects and engineers to ensure models and analyses align with broader data warehouse, data mart, and streaming data strategies.
• Rapidly adopt new tools, techniques, and languages to solve evolving analytical challenges.

Required Qualifications

• 5+ years of experience as a Data Scientist, Data Architect, or Database Administrator (DBA).
• Expert-level proficiency in Python and SQL.
• Strong experience with ESRI, Alteryx, Tableau, and/or other advanced visualization tools.
• Advanced knowledge of at least one scripting, ETL, or analysis language.
• Hands-on familiarity with modern machine learning frameworks and tools (e.g., scikit-learn, TensorFlow, XGBoost).
• Solid theoretical knowledge of machine learning model families: regression, decision trees, clustering, SVMs, and neural networks.
• Command of advanced mathematics including probability, statistics, calculus, and partial differential equations (PDEs).
• Extensive experience working with large-scale datasets, including those from Big Data and streaming platforms.
• Working knowledge of data architecture, data warehousing concepts, and data marts.
• Strong written and verbal communication skills, with the ability to present to executive and cross-functional audiences.

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