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Senior Director Data Science Jobs in Missouri (NOW HIRING)

(USA) Director, Data Science

Anderson, MO · On-site

$130K - $260K/yr

The (USA) Director, Data Science leads the development and execution of advanced data science strategies to drive business insights and innovation. This role oversees the design, testing, and ...

(USA) Director, Data Science

Noel, MO · On-site

$130K - $260K/yr

The (USA) Director, Data Science leads the development and execution of advanced data science strategies to drive business insights and innovation. This role oversees the design, testing, and ...

The (USA) Director, Data Science leads the development and execution of advanced data science strategies to drive business insights and innovation. This role oversees the design, testing, and ...

The Director, Data Science leads the development and deployment of advanced analytical models and data strategies to drive business value. This role requires expertise in machine learning, coding ...

(USA) Director, Data Science

Noel, MO · On-site

$130K - $260K/yr

The Director, Data Science leads the development and deployment of advanced analytical models and data strategies to drive business value. This role requires expertise in machine learning, coding ...

(USA) Director, Data Science

Anderson, MO · On-site

$130K - $260K/yr

The Director, Data Science leads the development and deployment of advanced analytical models and data strategies to drive business value. This role requires expertise in machine learning, coding ...

(USA) Director, Data Science

Noel, MO · On-site

$130K - $260K/yr

Position Summary We are seeking a highly experienced Director of Data Science & Machine Learning to ... Translate complex technical concepts into clear business outcomes for senior leadership. * Align ...

Position Summary We are seeking a highly experienced Director of Data Science & Machine Learning to ... Translate complex technical concepts into clear business outcomes for senior leadership. * Align ...

(USA) Director, Data Science

Anderson, MO · On-site

$130K - $260K/yr

Position Summary We are seeking a highly experienced Director of Data Science & Machine Learning to ... Translate complex technical concepts into clear business outcomes for senior leadership. * Align ...

(USA) Director, Data Science

Noel, MO · On-site

$130K - $260K/yr

As the Director of Data Science for the Walmart Data Ventures Tech team, you will lead the development and deployment of production-grade, end-to-end supplier-facing AI systems. You will spearhead ...

As the Director of Data Science for the Walmart Data Ventures Tech team, you will lead the development and deployment of production-grade, end-to-end supplier-facing AI systems. You will spearhead ...

(USA) Director, Data Science

Anderson, MO · On-site

$130K - $260K/yr

As the Director of Data Science for the Walmart Data Ventures Tech team, you will lead the development and deployment of production-grade, end-to-end supplier-facing AI systems. You will spearhead ...

Our partner is looking for a Director of Operations, Data Science based in Netherlands ... This is a senior, cross-functional role connecting business strategy, data science, technology, and ...

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Senior Director Data Science information

What does a senior director of data science do?

A Senior Director of Data Science leads and oversees the data science strategy for an organization, managing teams of data scientists, analysts, and engineers. They are responsible for aligning data initiatives with business goals, guiding advanced analytics projects, and ensuring the effective use of data to drive decision-making. This role often involves collaborating with other executives to develop data-driven solutions, establishing best practices, and setting the vision for how data science supports organizational growth.

How does a senior director of data science typically collaborate with other departments within an organization?

A Senior Director of Data Science frequently partners with leaders from product, engineering, marketing, and business strategy to align data-driven insights with organizational goals. They facilitate cross-functional collaboration by translating complex analytics into actionable business recommendations, ensuring that data science initiatives support top-level priorities. This role often leads a team of data scientists while serving as a bridge between technical teams and non-technical stakeholders, fostering a culture of data-informed decision-making throughout the company.

What are the key skills and qualifications needed to thrive as a senior director data science, and why are they important?

To thrive as a Senior Director Data Science, you need deep expertise in advanced analytics, machine learning, statistical modeling, and a strong educational background in a quantitative field, often with a master's or PhD. Familiarity with data platforms (like AWS, Azure), programming languages (such as Python, R), and leadership in deploying enterprise-level data solutions is vital, along with experience managing large teams. Exceptional strategic thinking, communication, and stakeholder management skills set top candidates apart in this role. These abilities are crucial for driving data-driven business strategies, leading high-performing teams, and ensuring impactful outcomes at the organizational level.

What is the difference between Senior Director Data Science vs Data Science Manager?

AspectSenior Director Data ScienceData Science Manager
ResponsibilitiesOversees multiple teams, sets strategic vision, aligns data science initiatives with business goalsManages day-to-day operations of data science teams, executes projects, and ensures deliverables
Required CredentialsAdvanced degree (Master's/PhD), extensive experience, leadership skillsRelevant degree, experience in managing data projects, technical expertise
Work EnvironmentStrategic, cross-departmental, executive collaborationOperational, team-focused, project management

The Senior Director Data Science typically holds a higher strategic leadership role, overseeing multiple teams and aligning data initiatives with company goals. In contrast, a Data Science Manager focuses on managing teams and executing projects. Both roles require strong technical backgrounds, but the Senior Director emphasizes strategic vision and leadership across departments.

What are popular job titles related to Senior Director Data Science jobs in Missouri?

For Senior Director Data Science jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Senior Director Data Science jobs in Missouri look for?

The top searched job categories for Senior Director Data Science jobs in Missouri are:

What cities in Missouri are hiring for Senior Director Data Science jobs?

Cities in Missouri with the most Senior Director Data Science job openings:

Senior Director, Data Science and AI - Services

Creve Coeur, MO • On-site


Cushman & Wakefield
Real Estate • 10K+ employees

7.4

Company rating: 7.4 out of 10

Based on 159 frontline employees who took The Breakroom Quiz

113th of 206 rated real estate companies

People enjoy working here

Good employer

Recommended by students


$204 - $240/hr

Other

Medical, Dental, Vision, Life, Retirement

Posted 11 days ago


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.

INCO: “Cushman & Wakefield”

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