Operational Data Scientist

Dematic; Grand Rapids (MI); On-site; USD 110,000 - 140,000; Full time

Job summary

Dematic is seeking a Data Scientist for our Operational Intelligence team to grow analytics capability at a pivotal time, blending advanced analytics, ML, and business problem solving to turn complex data into actionable insights that influence strategy.

You will partner with stakeholders across functions, design analytical solutions, and communicate findings to drive real outcomes. The role is hands-on, requiring model building as well as presenting insights to non-technical audiences.

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 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.

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

Skills

Python

SQL

R

ML model deployment

Cloud platforms

Communication skills

Self-starter

Collaborative

Tools

Databricks

Snowflake

Azure ML

Azure

AWS

GCP

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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