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### Director of MS in Business Analytics \& Data Science (open rank career track faculty position) AF7806
- 494068
- Stillwater
- SPEARS SCHOOL OF BUSINESS (STW)
- Faculty
- PhD
Oklahoma State University
Master of Business Analytics and Data Science Program
Program Director Position Announcement
The Spears School of Business at Oklahoma State University (OSU) invites applications and nominations for the position of Director of the MS in Business Analytics and Data Science (MS\-BAnDS) program. The preferred start date is Spring 2027, though an earlier or later start may be negotiated. The search will remain open until the position is filled.
Oklahoma State University’s Spears School of Business is home to a nationally ranked and highly reputed MS in Business Analytics and Data Science (MS\-BAnDS) program. It is a college level graduate program (somewhat like an MBA) whereby the classes are shared by faculty members in various departments. The program grew from our well\-established MS in MIS program as a collaboration between the School of Marketing and International Business and the Department of Management Science and Information Systems. Spears Business is looking to hire the next leader of this program. The Director provides strategic leadership to the Spears Business AI/Analytics/Data Science program. The faculty director will report to the Vice Dean for Graduate Programs and Research and focus on managing all aspects of the program in collaboration with the Watson Graduate School of Management (WGSM) team and faculty members from participating departments. They will also have an academic home in one of the Spears School of Business academic departments. It is an 11\-month open rank career track position. Salary is competitive for a comprehensive research university and contingent on available funding.
Responsibilities/Duties
Overall Program Leadership
- Serve as the main faculty point of contact and champion for the BAnDS program, working with the WGSM team to manage program operations across all venues.
- Partner with the Dean and Vice Dean on fundraising, Advisory Board relations, and alumni engagement to support program activities and scholarships.
Curriculum Leadership
- Lead strategic development, evaluation, revision, and maintenance of BAnDS program options, certificates, and offering venues (Stillwater, Tulsa, online, executive, and international), including curriculum design and accreditation assessment.
- Chair the BAnDS Core Faculty Committee; collaborate with SSB departments on scheduling, faculty team building, and cross\-program relationships in consultation with the Vice Dean.
- Drive student recruitment and retention by developing annual goals, a marketing plan, 4\+1 pipeline opportunities, and leading the ADS Admissions decision process.
- Teach in the program per expected workload expectations.
BAnDS Student/Staff Operations
- Manage graduate assistantships, scholarships, travel awards, internship approvals, and academic integrity matters.
- Oversee student orientation, competitions, professional development, and engagement opportunities for both full\-time and part\-time students.
- Track program enrollments, graduation rates, and coordinate alumni and employer outreach.
- Evaluate BAnDS\-specific staff and provide input on broader WGSM staff assessments.
Qualifications and Experience
- Earned doctorate in a closely related field.
- Demonstrated excellence in teaching, professional service, and research.
- Highly effective communication, interpersonal and leadership skills as evidenced by the ability to engage with faculty, students, staff, alumni, and the business community.
- Academic or industry experience that demonstrates planning, program development, evaluation, problem solving, external relations, and collaboration skills.
Academic Environment
OSU is a modern land\-grant institution with an interdisciplinary approach to programs that prepares students for success. Through leadership and service, OSU is preparing students for a bright future and building a brighter world for all. As Oklahoma's only university with a statewide presence, OSU improves the lives of people in Oklahoma, the nation, and the world through integrated, high\-quality teaching, research, and outreach. OSU has more than 35,000 students across its five\-campus system. The main campus is in Stillwater, a city of about 50,000 residents situated approximately 65 miles from both Oklahoma City and Tulsa, and approximately 250 miles from Dallas and Kansas City. OSU Stillwater has more than 24,500 students on its campus, representing all 50 states and more than 100 countries.
Stillwater is a diverse and welcoming academic and cultural community. Students and staff of OSU comprise about half of the city's population. Stillwater has been described as “America’s Friendliest College Town,” and has been listed as one of Money Magazine’s Best Places to Live. Stillwater boasts a historic downtown, a superb campus, highly rated public schools, and a regional airport with direct flights to and from Dallas\-Fort Worth. The city offers a variety of activities on campus and in the community, including music, drama, art, speakers, recreation, and sporting events. Examples include the McKnight Center for the Performing Arts, the Colvin Center, and the Seretean Wellness Center for physical education and recreation. Nearby lakes, walking/biking trails, and local/state parks are popular with students and faculty.
Additional Resources
- MS\-BAnDS program\- https://go.okstate.edu/graduate\-academics/programs/masters/business\-analytics\-and\-data\-science\-ms.html
- Spears School of Business \- https://business.okstate.edu/
- Oklahoma State University \- https://go.okstate.edu/
- OSU interactions with the Stillwater area \- https://go.okstate.edu/about\-osu/visit\-stillwater.html
- Information about the Stillwater area \- www.visitstillwater.org
Applications and Nominations:
Applications received by August 15, 2026, will receive priority consideration; however, application review will begin immediately and continue until the position is filled. Applications will be accepted online at jobs.okstate.edu.
Candidates should submit the following materials: letter of interest; statement of teaching, research, and service/outreach; summary of prior teaching evaluations; curriculum vitae; and list of three references.
Questions regarding this position or nominations, including the name, address, phone number, and email of the individual you are nominating, may be directed to:
Dr. Ramesh Sharda
ConocoPhillips Chair and Regents Professor of MSIS
Spears School of Business
383 Business Building \| Stillwater, OK 74078
Ph: 405\-744\-8850
Email: ramesh.sharda@okstate.edu
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Oklahoma State University, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,150.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Oklahoma State University AI Hiring
Oklahoma State University has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Stillwater, OK, US.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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