Data Scientist

Job Summary

Moultrie is seeking a Data Scientist to join the growing Data and Analytics Team. This role will develop predictive and prescriptive modeling capabilities that power decision-making across Moultrie.

Job Responsibilities

• Predictive and Prescriptive Modeling
• Design, build, and maintain predictive models addressing defined business questions (customer churn, subscription health, purchase propensity) using data from the foundational layer in Snowflake.
• Deliver model outputs as attributes that can integrate cleanly into downstream BI products (Tableau, Streamlit) and activation platforms (BlueConic, Braze, TripleWhale).
• Work with business stakeholders to translate ambiguous questions into scoped modeling problems with defined success metrics.
• Communicate model outputs and their business implications clearly to non-technical audiences.
• Track, document, and monitor experiments and deployed models to ensure outputs are reliable, understandable, and reproducible.

Job Requirements

• Skills and Qualifications
• 4+ years of hands-on experience in data science or a role with significant applied modelling.
• Demonstrated experience building and deploying predictive models in a business context.
• Strong Python proficiency: Proven experience using libraries (scikit-learn, pandas) to build and maintain predictive models.
• Experience with classification and regression techniques and the ability to validate model performance using appropriate metrics (precision, recall, AUC, etc.).
• SQL proficiency: Able to write clean, maintainable code for supporting models in Snowflake with support from data engineers.
• Experience with Git and standard software development practices: version control, code reviews, branching, and CI/CD basics.
• Ability to take an ambiguous business problem and work backwards to produce models that support effective solutions by creating a list of requirements and working through sprints to deliver.
• Strong documentation practices: able to produce and maintain model definitions, lineage documentation, and data dictionaries that enable other developers and business stakeholders.
• Collaborative working style: comfortable operating at the boundary between data engineering, data science, and business teams.

Preferred Qualifications

• Experience in retail, CPG, or consumer hardware.
• Hands-on experience with a feature store platform.
• Experience with MLflow or a comparable experiment tracking tool.
• Familiarity with Snowpark or Snowflake ML Functions.
• Experience delivering model outputs that can be used in BI tools and other downstream platforms.