Hybrid Data Scientist: ML & Analytics for Impact

Hollstadt & Associates; Arden Hills (MN); Hybrid; USD 57,000 - 81,000; Full time

Benefits offered by this job

Medical (individual or family)

Dental (individual or family)

Vision (individual or family)

Life insurance (individual or family)

Short-term disability

Long-term disability

Paid sick leave

Retirement benefits (plans)

401(k) match on first 4% of your\ncon(

$5,000 Longevity Award bonus for stay"

$1,000 referral bonus for recruiting a

Job summary

Hollstadt Consulting in Arden Hills, MN is seeking an Intermediate Data Scientist for a 6-month hybrid assignment, working on-site Tue-Thu in Arden Hills. The role partners with Corporate IT to apply statistical methods and machine learning to key business decisions that drive revenue growth and cost reduction.

As experience grows, you will own moderately complex analytical projects, develop models, run experiments, and translate findings into actionable recommendations while collaborating with

Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, or related field.
• 3–5 years of hands-on experience applying statistics, machine learning, experimentation, or decision science to business problems.
• Working knowledge of Python, R, and SQL, with experience using analytical platforms and model lifecycle tools such as Databricks and MLflow.
• Solid knowledge of statistical inference, experimental design, regression, forecasting, feature selection, model validation, uncertainty, and model monitoring.
• Demonstrated ability to frame moderately complex problems, align success criteria with business owners, quantify impact, and translate technical findings into clear insights and actionable recommendations.
• Industry knowledge in agriculture or related commercial settings, with the ability to connect business drivers to analytical decisions.

Responsibilities

• Partner with business stakeholders to frame use cases, understand industry drivers, and agree on decision needs and success criteria.
• Explore, profile, cleanse, transform, and integrate enterprise and reputable external data, verifying quality against source data, business rules, and industry context while following privacy, security, and sourcing requirements.
• Translate business requirements and domain knowledge into features, experiments, analytical workflows, and model evaluation criteria.
• Select, develop, compare, and refine statistical and machine learning models using sound statistical reasoning, business context, and reusable analytical components.
• Develop reproducible analytical workflows and evaluate and monitor model accuracy, bias, explainability, and performance drift against agreed business and technical criteria.
• Use approved AI tools to accelerate coding, testing, and documentation while remaining accountable for method selection, analytical quality, interpretation, and clear communication.
• Distinguish meaningful patterns from noise and communicate findings, assumptions, tradeoffs, uncertainty, risk, and quantified impact as clear business implications and practical recommendations.
• Support business owners in adopting recommendations and measuring results, while business owners retain accountability for adoption and operational decisions.
• Partner with product, engineering, platform, and business teams to plan incremental deliverables and support production integration, automated monitoring, or custom development when needed.
• Participate in analytical, model, and code reviews; document work and share statistical methods, domain insights, and reusable practices.

Skills

Statistical modeling

Experiment design

Model evaluation

Data storytelling

Business partnering

Education

Bachelor’s degree in related field

Tools

Databricks

MLflow

Job description

Hollstadt Consulting in Arden Hills, MN is seeking an Intermediate Data Scientist for a 6-month hybrid assignment, working on-site Tue-Thu in Arden Hills. The role partners with Corporate IT to apply statistical methods and machine learning to key business decisions that drive revenue growth and cost reduction.

As experience grows, you will own moderately complex analytical projects, develop models, run experiments, and translate findings into actionable recommendations while collaborating with