About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Transportation, Logistics, Supply Chain and Storage.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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What You’ll Do

Confidential Client is building a modern Operational Intelligence capability and is seeking an Operational Data Scientist to turn large operational datasets into production-quality analytics and machine learning solutions. This is a hands-on role that collaborates closely with business stakeholders to deliver measurable operational improvement.

• Develop, validate, and deploy machine learning and statistical models (regression, classification, clustering, forecasting) to support operational decision-making
• Design repeatable analytical pipelines and automated model deployment workflows within a cloud-based data platform
• Work with Databricks or similar cloud data tools to access, transform, and analyze large-scale distributed data
• Ensure data quality, lineage, and discoverability to support reliable analytics
• Translate complex analytical results into clear, actionable recommendations for technical and non-technical stakeholders
• Partner with operations, engineering, and product teams to scope problems, prioritize experiments, and measure impact
• Document solutions and contribute to analytics best practices as the team and capability mature

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What We’re Looking For

We're seeking candidates who combine practical machine learning experience with strong data-engineering and communication skills.

• Proven proficiency in Python and/or R, and strong SQL skills for data access and manipulation
• Hands-on experience building and deploying ML models in production (forecasting, classification, regression, clustering)
• Experience with cloud data platforms and distributed compute (Databricks, Snowflake, Azure/AWS/GCP)
• Comfortable working with large datasets and building scalable data pipelines
• Strong ability to explain technical results to business audiences and drive data-informed decisions
• Self-starter mindset, intellectual curiosity, and a pragmatic approach focused on business impact
• Bachelor’s degree in a quantitative field (or equivalent practical experience)

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Preferred Qualifications

These will help you move faster in the role but are not strict requirements.

• Prior experience in transportation, logistics, supply chain, or operations analytics
• Familiarity with model monitoring, MLOps tools, or deployment frameworks
• Experience with time-series forecasting and optimization use cases
• Knowledge of data cataloging, data governance, or data quality tooling

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Location & Work Authorization

• This role is based in Atlanta, GA (on-site / hybrid expectations to be confirmed by the client).
• Applicants must be authorized to work in the United States. Confidential Client will review work-authorization needs during the hiring process.

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Why This Role

• High-visibility, high-impact opportunity to help shape a modern analytics practice inside a large operations-led organization
• Work with modern cloud data platforms and production ML workflows
• Collaborate across functions and see your analytical work translate directly into operational improvements

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.