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Black Box Optimization Jobs (NOW HIRING)

Black Box

Workforce Management Manager

Plano, TX · On-site

Oversee scheduling frameworks for 24/7/365 data center operations, ensuring optimal coverage and ... Black Box is a leading global technology solutions provider with 2,500+ team members across 24 ...

Black Box

Senior Logistics Manager

Rayville, LA · On-site

... and process optimization. * Lead logistics related safety initiatives, ensure compliance with ... Black Box is a leading global technology solutions provider with 2,500+ team members across 24 ...

Black Box

Field Support Technician

Richmond, VA · On-site

$19.50 - $26.75/hr

This role will also coordinate with other groups within Black Box such as project managers, Smart ... Perform network closet clean-up, switch port optimization, and survey work as needed. Perform ...

Black Box Corporation

Field Support Technician

Richmond, VA · On-site

$19.50 - $26.75/hr

This role will also coordinate with other groups within Black Box such as project managers, Smart ... Perform network closet clean-up, switch port optimization, and survey work as needed. Perform ...

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Black Box Optimization information

See salary details

$16K

$55.8K

$102K

How much do black box optimization jobs pay per year?

As of Sep 12, 2026, the average yearly pay for black box optimization in the United States is $55,794.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,000.00 and $72,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals working in black box optimization and how can they be addressed?

Professionals in Black Box Optimization often encounter challenges such as limited information about the system being optimized, noisy data, and computationally expensive evaluations. To manage these, practitioners typically use surrogate models, parallel computing, and adaptive sampling to efficiently explore the solution space. Collaboration with domain experts is also vital to interpret results and refine optimization strategies, ensuring robust and meaningful outcomes. Staying updated on the latest optimization algorithms and software tools can further enhance performance and problem-solving capabilities.

What are the key skills and qualifications needed to thrive as a black box optimization specialist, and why are they important?

To thrive as a Black Box Optimization Specialist, you typically need a strong background in mathematics, statistics, and computer science, often supported by a relevant degree. Familiarity with optimization software (such as MATLAB or Python libraries like SciPy), machine learning frameworks, and sometimes domain-specific tools is essential. Strong analytical thinking, problem-solving abilities, and collaborative communication skills help you stand out in this role. These skills enable effective analysis and optimization of complex systems where internal mechanisms are unknown, leading to impactful solutions in fields like engineering, finance, and AI.

What is the difference between Black Box Optimization vs Data Scientist?

AspectBlack Box OptimizationData Scientist
Required CredentialsTypically a degree in mathematics, computer science, or engineering; certifications in optimization or data analysisDegree in statistics, computer science, or related fields; certifications in data analysis or machine learning
Work EnvironmentResearch labs, R&D departments, tech companies focusing on algorithm developmentBusiness environments, tech firms, consulting, analyzing data to inform decisions
Industry UsageUsed in engineering, AI, machine learning, and operations researchApplied across finance, healthcare, marketing, and technology sectors

Black Box Optimization and Data Scientists often share skills in programming and analytical thinking. While Black Box Optimization focuses on developing algorithms to optimize complex systems without explicit models, Data Scientists analyze and interpret data to generate insights. Both roles are vital in data-driven industries but serve different purposes within the analytics ecosystem.

What other helpful pages are available for Black Box Optimization?

Other pages related to Black Box Optimization:

Infographic showing various Black Box Optimization job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 89% Full Time, 8% Part Time, and 2% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution, with an average salary of $55,794 per year, or $26.8 per hour.

Workforce Management Manager

Plano, TX • On-site

Black Box
See more jobs at Black Boxexternal

Full-time

Re-posted 14 days ago

Job description


The Manager of Workforce Management (WFM) is responsible for designing, implementing, and optimizing workforce strategies that support data center operations at scale. This role ensures the right technical talent is available at the right time to meet uptime, capacity, and service-level objectives. The position partners closely with Data Center Operations, Capacity Planning, HR, and Finance to drive forecasting accuracy, staffing efficiency, and labor cost optimization across multiple sites or regions.
Key Responsibilities
  • Develop short- and long-term workforce plans aligned with data center growth, capacity expansion, and operational demand.
  • Build and maintain forecasting models for technician staffing, shift coverage, and project-based labor needs.
  • Partner with capacity planning teams to align workforce supply with infrastructure demand.
  • Oversee scheduling frameworks for 24/7/365 data center operations, ensuring optimal coverage and compliance.
  • Implement standardized WFM processes across multiple facilities or regions.
  • Monitor real-time staffing levels and adjust to meet SLAs, uptime requirements, and incident response needs.
  • Lead workforce analytics including headcount modeling, productivity metrics, utilization rates, and labor cost analysis.
  • Develop dashboards and reporting for executive visibility into workforce performance.
  • Use data-driven insights to recommend staffing optimizations and efficiency improvements.
  • Own and optimize WFM tools (e.g., scheduling systems, forecasting software, timekeeping platforms).
  • Drive automation and digital transformation initiatives within workforce planning processes.
  • Ensure integration between WFM systems and HRIS, ticketing, and capacity management tools.
  • Partner with HR on hiring strategies, talent pipelines, and workforce scalability.
  • Work with Finance to manage labor budgets, cost forecasting, and variance analysis.
  • Collaborate with Data Center Operations leadership to align workforce plans with maintenance schedules, deployments, and incident management.
Required
  • Bachelor's degree in Business, Operations, Engineering, or related field.
  • 8-12+ years of experience in Workforce Management, Operations Planning, or similar roles.
  • 3-5+ years of leadership experience managing WFM or operations teams.
  • Experience supporting 24/7 mission-critical environments (data centers, telecom, cloud, or similar).
  • Strong analytical and modeling skills (Excel, SQL, or similar tools).
  • Experience with WFM platforms (e.g., Kronos/UKG, NICE, Workday, or similar).
  • Experience in hyperscale or colocation data center environments.
  • Knowledge of capacity planning and infrastructure lifecycle management.
  • Familiarity with ITIL, incident management, or service operations frameworks.

Why Black Box?
Black Box is a leading global technology solutions provider with 2,500+ team members across 24 countries. We design, deploy, and manage world-class IT infrastructure solutions for some of the most demanding environments worldwide. We value innovation, ownership, transparency, and continuous growth-both in our business and our people. When you join Black Box, you join a team committed to delivering excellence and elevating the customer experience.
Equal Opportunity Employer- Black Box is an equal opportunity employer. We welcome applicants of every background and do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected status.

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