Intermediate Data Scientist

Hollstadt Consulting is a management and technology consulting firm dedicated to placing professionals at engagements where they will excel. When you work with us, you'll work with a refreshingly real company led and staffed by seasoned experts who are also down-to-earth, good people. We're committed to treating you with respect and helping you achieve your career aspirations.

Since 1990, Hollstadt has been a trusted partner to more than 150 domestic and global companies and has successfully completed over 3,000 projects. Our continued growth has created challenging and rewarding opportunities for accomplished IT and Business Consultants. Hollstadt Consulting is an equal opportunity employer including disability/veteran.

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Role
:
Intermediate Data Scientist

Duration
: 6 months

Location
:
Hybrid in Arden Hills, MN
- Tuesday-Thursday

Rate
: up to $50.31/hour W2, dependent on skills and qualifications

Our client is looking for an Intermediate Data Scientist to join Corporate IT. This role is based in Arden Hills, MN and requires hybrid attendance in the office Tuesday through Thursday. This position is responsible for partnering with functions and lines of business to apply statistical methods, machine learning, and industry knowledge to key business decisions that support revenue growth and cost reduction.

With growing autonomy and guidance appropriate to project complexity, this position owns moderately complex analytical projects or defined components of larger initiatives, develops models and experiments, and translates findings into actionable recommendations. The role emphasizes statistical and machine learning expertise, business partnership, and industry knowledge rather than custom software development.

• 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…