A Data Scientist utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management.
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. Equal Opportunity Employer This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.
