Data Scientist

Overview:

The Data Scientist is responsible for leveraging advanced analytics, statistical models, and machine learning techniques to uncover insights from structured and unstructured data. This role supports decision-making across departments by developing predictive models, visualizations, and data-driven strategies that enhance business performance and operational efficiency. This role serves as a critical link between data and decision-making, collaborating with business leaders, operational teams, and technologists to uncover and communicate meaningful insights.

Essential Functions:

1. Data Science & Modeling: 60%

• Designs and executes data experiments to validate hypotheses and measure model performance.
• Designs, develops, and deploys machine learning (ML) models within Snowflake-based data pipelines and workflows.
• Conducts large-scale statistical analyses and controlled experiments to uncover actionable insights.
• Explores and analyzes structured and unstructured data to detect trends, anomalies, and opportunities.
• Turns broad or unclear problems into actionable projects by defining success metrics and setting clear goals for analysis.
• Collects, cleans, and prepares data for modeling and analysis to ensure data integrity and quality.
• Partners with Data Engineers to integrate and deploy analytical models and products into production environments.
• Translates high-priority business challenges into analytical strategies and data models that drive measurable return on investment (ROI).

2. Stakeholder Engagement & Innovation: 25%

• Visualizes complex data and crafts compelling, audience-tailored narratives for stakeholders at all levels—from frontline teams to executive leadership.
• Communicates findings in a clear, actionable manner that informs strategic decisions across the business.
• Stays informed on emerging AI/ML advancements and evaluates their potential to enhance business outcomes.

3. Performs other duties as assigned. 15%

Education and Experience:

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science or related field.
• 4 years of experience in hands-on data science, including modeling, visualization, and end-to-end project ownership.
• Experience with data in construction, field services, or operations-heavy environments preferred.

Skills/Abilities:

• Strong problem-solving mindset with the ability to navigate ambiguity, rapidly prototype solutions, and iterate based on feedback.
• Able to communicate technical concepts to non-technical stakeholders in a clear, compelling, and engaging manner.
• Demonstrated ability to collaborate effectively within agile, cross-functional teams. 
• Proficient in Python, SQL (Snowflake preferred), and data wrangling in large-scale environments.
• Familiarity with cloud data warehouses and MLOps best practices (bonus if you’ve used Airflow, or similar tools).
• Skilled in ML techniques (e.g., regression, classification, clustering, and ensemble methods).
• Previous exposure to deep learning, Natural Processing Language (NLP), and computer vision is a plus. 

Work Environment:

• Office environment.

Physical Demands:

• Prolonged periods of sitting at a desk and working on a computer.
• Must be able to lift up to 15 pounds at times.