Data Analyst (Hybrid Remote)

Schedule: Tues-Thursday onsite, full-time

TradeTrax provides the real-time job site intelligence and actionable reports production Builders and Trades need to boost the efficiency and profitability of their construction processes. This platform delivers comprehensive visibility into job site activity and unprecedented analytics of the construction process, so Builders and Trades can optimize operations, maximize resources, and build homes faster and better than ever.

The Data Analyst position at TradeTrax is vital in converting complex, business, customer, and TradeTrax platform technical data into actionable insights. These insights are essential for enhancing operational efficiency and informing strategic decision-making by our customers and our internal stakeholders, allowing them to unlock the full potential of the TradeTrax platform. The role requires a blend of technical expertise and business acumen to provide advanced analytics and reporting across our integrated technology stack. The ideal candidate will have advanced proficiency in data analysis and business intelligence tools, as well as experience with predictive analytics and data modeling.

Responsibilities:

• Conduct deep-dive analyses on complex datasets, using advanced analytical techniques to derive insights.
• Design, build, and deliver reports, dashboards and data visualizations that empower our customers to unlock the full potential of the TradeTrax platform.
• Analyze customer data (qualitative and quantitative) to uncover trends, provide actionable insights, and identify opportunities for improvement.
• Develop and maintain a repository of standardized and customized reporting templates for efficiency and consistency.
• Communicate complex data insights effectively to stakeholders across the organization, including non-technical audiences.
• Partner with various departments (e.g., marketing, sales, product, operations) to understand business needs and align data projects with organizational goals.
• Perform ad-hoc and in-depth analyses and translate them into insights that can be interpreted and actioned by business executives and stakeholders.
• Partner with internal technical teams to address data gaps, improve data quality, and enhance reporting capabilities.
• Design, develop, optimize, and deploy traditional machine learning and deep learning algorithms, models, and applications.
• Implement forecasting techniques to predict construction project timelines, focusing on reducing days under construction for new homes.
• Develop and implement machine learning (ML) models to extract insights from data.