Operational Data Scientist

Dematic; Wauwatosa (WI); On-site; USD 105,000 - 155,000; Full time

Job summary

Dematic in Wisconsin seeks a Data Scientist to join the Operational Intelligence team. You will grow data and analytics capability, turning complex datasets into actionable insights that influence strategy and performance.

Partner with stakeholders to frame problems, design analytical solutions, and present findings to non-technical audiences. This hands-on role combines building models with communicating outcomes to drive impact.

Qualifications

• Proficiency in Python and/or R with strong SQL skills.
• Experience building and deploying ML models (regression, classification, clustering, forecasting).
• Experience with cloud-based data platforms; familiarity with Databricks, Snowflake, Azure ML is a plus.
• Comfort with large-scale distributed data in cloud environments (Azure, AWS, GCP).
• Strong communication to translate analyses into business impact.
• Self-starter with ability to work in ambiguity; collaborative mindset.

Responsibilities

• Develop, validate, and deploy ML models to support operational decision-making.
• Collaborate with business partners to frame problems and translate outputs into actions.
• Work within a modern cloud-based data platform to access and analyze data at scale.
• Contribute to repeatable analytical frameworks, pipelines, and best practices.
• Ensure data quality and discoverability across the analytics environment.
• Communicate complex findings to technical and non-technical audiences.
• Demonstrate the value of analytics to foster a data-driven culture.

Skills

Python or R

SQL

ML model development

Cloud platforms

Data analytics storytelling

Communication skills

Self-starter

Collaboration

Tools

Databricks

Snowflake

Azure ML

Job description

We are looking for a Data Scientist to join our Operational Intelligence team, growing data and analytics capability at an exciting time as this is an opportunity to help shape a modern analytics practice within an established enterprise. You will work at the intersection of advanced analytics, machine learning, and business problem-solving, turning complex datasets into actionable insights that directly influence strategy and performance.

You will partner closely with business stakeholders across functions to understand their challenges, design analytical solutions, and communicate findings in ways that drive real outcomes. This is a high-impact, hands-on role suited for someone who is as comfortable building and deploying models as they are presenting insights to non-technical audiences.

Key Responsibilities

• Develop, validate, and deploy machine learning and statistical models to support operational decision-making

• Collaborate with business partners to frame problems, identify data needs, and translate analytical outputs into actionable recommendations

• Work within a modern cloud-based data platform environment (including Databricks) to access, transform, and analyze data at scale

• Contribute to the development of repeatable analytical frameworks, pipelines, and best practices as the team matures

• Ensure data quality and discoverability across the analytics environment

• Communicate complex findings clearly to both technical peers and non-technical stakeholders

• Help build a data-driven culture by demonstrating the value of analytics through practical, high-visibility work

Tasks and Qualifications

Skills & Capabilities

• Proficiency in Python and/or R, with strong SQL skills for data access and manipulation

• Demonstrated experience building and deploying ML models (regression, classification, clustering, forecasting)

• Experience with cloud-based data platforms; familiarity with Databricks or similar tools (e.g., Snowflake, Azure ML) is a plus

• Comfort working with large-scale distributed data in a cloud environment (Azure, AWS, or GCP)

• Strong communication skills with the ability to translate analytical work into business impact

• A self-starter mindset that is comfortable with some ambiguity and energized by the chance to build something meaningful

• A collaborative, intellectually curious approach with a bias toward practical application over theoretical elegance

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