Data Scientist: Predictive Modeling & Feature Store

EBSCO Industries, Inc.; Birmingham (AL); On-site; USD 110,000 - 150,000; Full time

Job summary

Moultrie, headquartered in Birmingham, AL, is a leader in game feeders and cellular camera innovation, delivering real-time remote monitoring solutions for hunters and property owners. Moultrie’s Data and Analytics team seeks a Data Scientist to own predictive and prescriptive modeling, develop feature stores, and deploy models into BI-ready outputs using Snowflake, MLflow, and Python.

You will collaborate with data engineers and business partners to turn ambiguous questions into measurable

Qualifications

• Hands-on data science experience with predictive modeling.
• Ability to build and deploy models in business contexts.
• Proficiency in Python with ML libraries (scikit-learn, pandas).
• Strong SQL for Snowflake data modeling and data preparation.
• Experience with model evaluation metrics (AUC, precision, recall).
• Collaboration with cross-functional teams to deliver BI-ready outputs.

Responsibilities

• Design, build, and maintain predictive models addressing business questions.
• Deliver model outputs to BI tools and activation platforms.
• Translate ambiguous questions into scoped modeling problems with defined metrics.
• Document experiments and model deployments for reproducibility.
• Collaborate with data engineers to support feature engineering and training datasets.

Skills

Python proficiency

SQL

Git

Data science

scikit-learn

Pandas

Tools

Snowflake

Snowpark

MLflow

Tableau

Streamlit

dbt

Snowflake ML Functions

Job description

Moultrie, headquartered in Birmingham, AL, is a leader in game feeders and cellular camera innovation, delivering real-time remote monitoring solutions for hunters and property owners. Moultrie’s Data and Analytics team seeks a Data Scientist to own predictive and prescriptive modeling, develop feature stores, and deploy models into BI-ready outputs using Snowflake, MLflow, and Python.

You will collaborate with data engineers and business partners to turn ambiguous questions into measurable