Data Scientist

Role Purpose

The Data Scientist will serve as a hands-on applied data science contributor within the Business Intelligence team. They will work closely with market intelligence teammates, business stakeholders, and leadership to develop practical analytical solutions that improve how we understand markets, customers, competitors, and business performance.

Key Responsibilities

• Develop and deliver applied data science solutions for business intelligence use cases such as forecasting, classification, segmentation, anomaly detection, and other predictive or descriptive analytics.
• Own end-to-end analytical execution, including data ingestion, API integration, transformation of structured and semi-structured data, feature engineering, modeling, validation, and stakeholder-ready output creation.
• Partner with market intelligence teammates and business stakeholders to frame ambiguous questions, define fit-for-purpose analytical approaches, and translate outputs into practical recommendations.
• Select appropriate statistical, machine learning, and AI methods based on business need, data constraints, interpretability, and time-to-insight; avoid unnecessary complexity when simpler approaches are sufficient.
• Apply rigorous validation and reasonableness checks to ensure outputs are accurate, explainable, and aligned with market and business context.
• Build scalable, reusable workflows in Databricks and related tools that improve reproducibility, speed, and team efficiency.
• Prepare clear visualizations, dashboards, and executive-ready materials in Power BI, Excel, and PowerPoint to communicate methods, insights, assumptions, and implications effectively.
• Partner closely with business-facing teammates to strengthen quantitative rigor in market intelligence, competitive intelligence, strategic finance, and economics-oriented analyses.
• Stay current with the evolving data science and AI landscape and contribute ideas for applying new methods and tools where they may create business value.
• Contribute to best practices for experimentation, documentation, model validation, code quality, and reproducible analytical workflows within the BI analytics team.
• Participate in agile delivery, code reviews, documentation, and production support for analytical solutions.

Experiences/Education - Required

• Bachelor’s degree in data science, statistics, computer science, economics, operations research, engineering, or related quantitative field
• Minimum 3 years of experience applying data science, machine learning, or advanced analytics to business problems in a production or business-facing environment
• Strong proficiency in Python and SQL, with experience supporting the analytical workflow from data ingestion and preparation through model output and stakeholder-ready delivery
• Advanced proficiency in Excel and PowerPoint, including building structured analyses and communicating executive-ready insights

Experiences/Education - Desired

• Experience using Databricks and/or Spark for large-scale data processing, modeling, and analytics workflows
• Experience building dashboards or analytical products in Power BI
• Experience with version control, CI/CD, model lifecycle practices, or reproducible analytics workflows
• Familiarity with business intelligence, market intelligence, competitive intelligence, strategic finance, and/or economics-oriented applications of analytics
• Experience evaluating and applying emerging AI or machine learning approaches in practical business settings

Pay Range

$97,314.00 - $133,808.00 assuming full time status. Starting pay for the successful applicant is dependent on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education.