Hybrid Data Scientist: Agriculture ML & Analytics

Ledelsea; Minneapolis (MN); Hybrid; USD 95,000 - 130,000; Full time

Job summary

Ledelsea is seeking an Intermediate Data Scientist to join Corporate IT in Arden Hills, MN. The role is hybrid, requiring in-office presence Tuesday through Thursday, with local candidates preferred.

The candidate will apply statistical methods and machine learning to drive revenue growth and cost reduction, partnering with business units and engineering teams to deliver measurable impact.

Qualifications

• Bachelor's degree in a data-related field.
• 3-5 years of hands-on experience applying statistics, ML, experiments, or decision science to business problems.
• Proficient in Python, R, and SQL with capability to review code and outputs.
• Solid knowledge of statistical inference, experiments, regression, classification, forecasting, feature selection, model validation, uncertainty, and monitoring.

Responsibilities

• Partner with stakeholders to frame use cases, decide success criteria, and align on decision needs.
• Profile, cleanse, transform, and integrate data while ensuring privacy and data quality.
• Translate business requirements into features, experiments, and analytical workflows.
• Develop and compare ML models with sound statistical reasoning and business context.
• Monitor model performance, explainability, and bias; document methods and results.
• Collaborate with product, engineering, and business teams for production integration.

Skills

Python

R

SQL

Statistical modeling

Education

Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, or related field

Tools

Databricks

MLflow

Job description

Ledelsea is seeking an Intermediate Data Scientist to join Corporate IT in Arden Hills, MN. The role is hybrid, requiring in-office presence Tuesday through Thursday, with local candidates preferred.

The candidate will apply statistical methods and machine learning to drive revenue growth and cost reduction, partnering with business units and engineering teams to deliver measurable impact.