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Data Operations Director Jobs in O Fallon, MO (NOW HIRING)

The Director partners closely with agents, Contract Truckmen, customers, and internal teams to ... Results-oriented leaders who use data and operational insights to drive continuous improvement.

The Director partners closely with agents, Contract Truckmen, customers, and internal teams to ... Results-oriented leaders who use data and operational insights to drive continuous improvement.

Direct the annual merit and bonus processes * Leading our HR Operations team focused on building ... Intermediate/Advanced Excel with strong data analytics skill set * Track record of working cross ...

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Data Operations Director information

See O Fallon, MO salary details

$48.6K

$120.2K

$187.1K

How much do data operations director jobs pay per year?

As of Sep 6, 2026, the average yearly pay for data operations director in O Fallon, MO is $120,233.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,900.00 and $153,000.00 per year, depending on experience, location, and employer.

What does a Data Operations Director do?

A Data Operations Director is responsible for overseeing the management, organization, and optimization of a company's data-related processes and teams. They ensure data quality, security, and accessibility, while aligning data management with business goals. This role often involves supervising data analysts, engineers, and other professionals, and implementing strategies for data governance and compliance. The Data Operations Director also collaborates with other departments to support data-driven decision making and operational efficiency.

How does a Data Operations Director typically collaborate with cross-functional teams to ensure data integrity and accessibility?

A Data Operations Director works closely with IT, data engineering, analytics, and business units to establish robust data governance practices and streamline data workflows. They often lead efforts to standardize data definitions, enforce quality controls, and implement access protocols to ensure that stakeholders across the organization can use reliable data for decision-making. Regular meetings, project management tools, and clear communication channels are essential for aligning priorities and resolving data-related issues efficiently. This cross-functional collaboration is key to maintaining high data integrity and fostering a data-driven culture.

What are the key skills and qualifications needed to thrive as a Data Operations Director, and why are they important?

To thrive as a Data Operations Director, you need expertise in data management, analytics, process optimization, and a relevant degree such as in computer science, statistics, or information systems. Familiarity with data warehousing solutions, ETL tools, cloud platforms (like AWS or Azure), and certifications such as Certified Data Management Professional (CDMP) are commonly required. Leadership, strategic thinking, and strong communication skills are essential for driving cross-functional teams and aligning data initiatives with business goals. These capabilities ensure efficient, secure, and high-quality data operations that support informed decision-making and organizational growth.

What is the difference between Data Operations Director vs Data Analyst?

AspectData Operations DirectorData Analyst
Required CredentialsBachelor's or Master's in Data Science, Business, or related field; experience in data managementBachelor's in Data Science, Statistics, or related field; proficiency in data analysis tools
Work EnvironmentLeadership role overseeing data teams, strategic planningAnalyzing data sets, generating reports, supporting decision-making
Employer & Industry UsageUsed in organizations with large data operations, tech, finance, healthcareCommon across various industries for data insights and reporting

The Data Operations Director focuses on managing data teams and strategic data initiatives, while the Data Analyst concentrates on analyzing data to generate insights. Both roles require strong data skills, but differ in scope and responsibilities.

What job categories do people searching Data Operations Director jobs in O Fallon, MO look for?

The top searched job categories for Data Operations Director jobs in O Fallon, MO are:

What cities near O Fallon, MO are hiring for Data Operations Director jobs?

Cities near O Fallon, MO with the most Data Operations Director job openings:

Infographic showing various Data Operations Director job openings in O Fallon, MO as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $120,233 per year, or $57.8 per hour.

Senior Director, Data Science and AI - Services

Cushman & Wakefield

Creve Coeur, MO • On-site

$204 - $240/hr

Other

Medical, Dental, Vision, Life, Retirement

Posted 18 days ago


Cushman & Wakefield rating

7.4

Company rating: 7.4 out of 10

Based on 159 frontline employees who took The Breakroom Quiz

113th of 209 rated real estate companies


Job description

Job Title

Senior Director, Data Science and AI - Services

Job Description Summary

The Senior Director, Data Science & AI - Services is a senior technical leader responsible for executing the organization's AI strategy. This role leads a multidisciplinary team of data scientists, ML engineers, and AI practitioners to build, deploy at scale, operate, and govern AI solutions across the enterprise. The Director champions AI innovation across the enterprise — spanning traditional machine learning, generative AI, and agentic systems — while maintaining the operational rigor, governance frameworks, and ethical standards required of a modern AI-driven organization.

Job Description AI Model Development
  • Lead the end-to-end architecture, development, and deployment of AI, including machine learning, GenAI, and Agentic models that are tailored to business use cases.
  • Drive the development of agentic AI systems — including multi-agent orchestration, tool-use, and autonomous task-execution pipelines — to automate complex enterprise workflows.
  • Establish model development standards encompassing data preprocessing, feature engineering, model selection, hyperparameter tuning, evaluation, and documentation.
  • Partner with data engineering teams to ensure robust, scalable, and high-quality data pipelines that support model training and inference.
AI Operations (MLOps / LLMOps)
  • Mature the organization's AIOps (MLOps & LLMOps) capabilities, including CI/CD pipelines for model training, evaluation, deployment, and monitoring.
  • Define and enforce standards for model versioning, experiment tracking, reproducibility, and model registry management
  • Implement robust model monitoring frameworks to detect performance degradation, data drift, concept drift, and bias in production systems, with automated alerting and retraining triggers.
  • Manage cloud AI/ML platform costs and optimize infrastructure utilization across training, fine-tuning, and inference workloads.
AI Innovation
  • Serve as an internal AI innovation champion — identifying high-value use cases across business functions and translating them into AI-powered solutions.
  • Build and maintain an enterprise AI roadmap aligned with strategic business objectives, balancing quick wins with long-term capability building.
  • Foster a culture of experimentation through structured ideation programs, hackathons, and proof-of-concept sprints, ensuring rapid validation and responsible scaling of AI initiatives.
  • Collaborate with product and technology leadership to embed AI capabilities into core enterprise capabilities and customer-facing products.
AI Governance
  • Partner, support, and execute the organization's AI governance framework, including policies for model risk management, fairness, explainability, privacy, and security.
  • Lead AI risk assessments and ensure all models in production meet internal standards and applicable regulatory requirements.
  • Partner with Legal, Compliance, and Risk teams to manage data privacy obligations (GDPR, CCPA), intellectual property considerations for generative AI outputs, and third-party AI vendor due diligence.
  • Champion sound AI principles organization-wide, ensuring that human oversight and accountability are embedded in every stage of the AI development lifecycle.
Team Leadership & Talent Development
  • Recruit, develop, and retain a high-performing team of AI practitioners.
  • Establish clear team structure, career paths, and performance frameworks that reward both technical excellence and collaborative impact.
  • Foster a team culture that values intellectual curiosity, rigorous experimentation, continuous learning, and collaboration.
  • Serve as a technical mentor and thought leader for technical and business teams in Technology and across the business.
Stakeholder Engagement
  • Build strong cross-functional partnerships with technology and business unit leaders to ensure AI initiatives are well-defined and aligned with business priorities.
  • Define and track KPIs and OKRs for the Data Science & AI function, providing regular reporting on model performance, operational health, and business impact to teams and leaders across the organization.
Education
  • Bachelor's degree in a quantitative field (Finance, Economics, Mathematics, Engineering, Computer Science, etc.) or a bachelor’s degree with related applied quantitative experience.
  • Master's degree in quantitative, arts, or business field preferred.
Experience
  • 6-8 years of progressive experience in data science, AI/ML engineering & data, 1+ years of experience with generative AI and Agentic systems, with at least 4+ years in a people leadership role.
  • Demonstrated track record of delivering production AI/ML systems at enterprise scale, from inception through deployment and ongoing operations.
  • Hands-on experience with generative AI, large language models, and prompt engineering in an enterprise context.
  • Experience building or scaling agentic AI systems.
  • Proven experience establishing MLOps/LLMOps practices.
  • Background in AI governance, model risk management, or responsible AI frameworks is highly desirable.

Cushman & Wakefield also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health, vision, and dental insurance, flexible spending accounts, health savings accounts, retirement savings plans, life, and disability insurance programs, and paid and unpaid time away from work. In addition to a comprehensive benefits package, Cushman and Wakefield provide eligible employees with competitive pay, which may vary depending on eligibility factors such as geographic location, date of hire, total hours worked, job type, business line, and applicability of collective bargaining agreements.

The compensation that will be offered to the successful candidate will depend on factors such as whether the position is covered by a collective bargaining agreement, the geographic area in which the work will be performed, market pay rates in that area, and the candidate’s experience and qualifications.

The company will not pay less than minimum wage for this role.

The compensation for the position is: $ 204,000.00 - $240,000.00

Cushman & Wakefield is an Equal Opportunity employer to all protected groups, including protected veterans and individuals with disabilities. Discrimination of any type will not be tolerated.

In compliance with the Americans with Disabilities Act Amendments Act (ADAAA), if you have a disability and would like to request an accommodation in order to apply for a position at Cushman & Wakefield, please call the ADA line at 1-888-365-5406 or email Accommodations@cushwake.com. Please refer to the job title and job location when you contact us.

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