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:
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.