Brandeis Online
Dr. Keishalee Shaw on the Future of Applied Data Science and Decision Analytics
Date xx, 2026
Discover how program chair Dr. Keishalee Shaw leads Brandeis Online's Applied Data Science and Decision Analytics program — uniting technology, ethics, and innovation to prepare students for data-driven leadership in today's digital AI economy.
What is your current job title? How would you describe your role?
My work sits at the intersection of a few different worlds, and I think that's what makes it so energizing. I'm the Founder and Principal of STRATA Responsible AI, where I advise organizations on what it actually takes to move from broad AI principles to practical governance, the frameworks, the operational controls, the audit-ready processes that let organizations adopt AI confidently and responsibly. Before founding STRATA, I spent over a decade at Blue Cross Blue Shield of Massachusetts working on enterprise AI governance efforts, supporting generative AI risk assessments, and partnering across engineering, legal, compliance, and product teams. That experience gave me a frontline view of where AI governance succeeds, and where it quietly fails.
At Brandeis University, I'm an adjunct professor and program chair for the Master of Science in Applied Data Science and Decision Analytics. In that role, I'm not just teaching; I'm helping shape the program, what students learn, and how those learning experiences connect to real professional challenges. I hold a Ph.D. in Strategic Leadership, graduate degrees in healthcare management and analytics, and certifications in AI product design and responsible innovation. Across all of these roles, the throughline is the same: helping people and organizations harness data and AI in ways that are not just technically powerful, but ethically sound and strategically grounded.
Why did you decide to get involved in the leadership of the Applied Data Science and Decision Analytics program at Brandeis Online?
Honestly? Because I kept seeing the same gap, and it frustrated me. Organizations were trying to scale AI, but they didn't have enough professionals who could sit at the intersection of technical skill, strategic thinking, and ethical judgment. They had great data engineers who didn't know how to communicate findings to leadership. They had smart analysts who had never thought seriously about bias or governance. And they had executives who wanted to be data-driven but lacked the translators who could bridge the technical and the strategic.
I've spent my career working in that gap, and I believe deeply that education is one of the most powerful levers for closing it. When the opportunity came to help design a program at Brandeis that could build exactly those kinds of professionals, people who can engineer a system and audit it for bias, who can build a dashboard and tell a compelling story with it, who can deploy a machine learning model and govern it responsibly, I didn't hesitate. Brandeis has a longstanding commitment to social justice, ethical inquiry, and academic rigor. That alignment with my own values made the decision easy.
“I kept seeing the same gap, and it frustrated me. Organizations were trying to scale AI, but they didn't have enough professionals who could sit at the intersection of technical skill, strategic thinking, and ethical judgment … I've spent my career working in that gap, and I believe deeply that education is one of the most powerful levers for closing it.”
What makes Brandeis Online’s MS in Applied Data Science and Decision Analytics unique? What sets it apart from similar programs at other schools?
Most data science programs are excellent at developing either technical depth or analytical breadth, but very few do both while weaving in responsible AI and governance as genuine requirements rather than optional electives.
That's where we're different. Brandeis foregrounds ethical, sustainable, and applied AI within an integrated, workforce-aligned degree. Responsible AI isn't an add-on; it runs through every course like a spine.
We also take sustainability seriously in a way that's genuinely rare. Students don't just learn to build data pipelines; they learn to evaluate those systems for energy efficiency and carbon impact. They learn that the environmental cost of large model training is a governance question, not just an engineering one. And they leave knowing how to design cloud architectures with built-in sustainability metrics. That's forward-looking in a way that reflects where industry and regulation are heading.
Finally, the program is unapologetically applied. Every assessment mirrors real workforce deliverables: executive memos, governance audits, model deployment reports, and interactive dashboards. Our students graduate with a portfolio, not just a transcript.
“The program is unapologetically applied. Every assessment mirrors real workforce deliverables: executive memos, governance audits, model deployment reports, and interactive dashboards. Our students graduate with a portfolio, not just a transcript.”
Why is applied data science important now?
The numbers tell part of the story. Between September 2024 and September 2025, U.S. employers posted over 88,000 openings for master's-level professionals in data science, statistics, and operations research, at a median salary of $140,200 with 7.7% annual growth. Fast-growing skills include Python, machine learning, data analysis, and R. The Boston metro alone posted over 5,600 data-focused positions in the past year, drawing from healthcare, finance, higher education, and technology.
But the numbers don't capture the deeper urgency. We are at a moment when AI is being embedded in consequential decisions, such as who gets a loan, who receives a diagnosis, who gets flagged by an algorithm in a hiring process, and how we allocate energy resources. And we don't yet have enough professionals who know how to build these systems responsibly. Gartner has estimated that 60% of AI projects will be abandoned by 2026 due to inadequate data foundations, and that 63% of organizations report a lack of clarity about what "AI-ready data" even means. That is a crisis of talent and governance at scale.
This program directly addresses that crisis. We are training the professionals who will close the gap between AI ambition and AI accountability, not because it's a nice thing to have, but because it's essential for organizations that want to deploy AI sustainably, ethically, and at scale.
“We are training the professionals who will close the gap between AI ambition and AI accountability, not because it's a nice thing to have, but because it's essential for organizations that want to deploy AI sustainably, ethically, and at scale.”
What skills will applied data science students gain that will make them competitive in the workforce?
Graduates of the MS in Applied Data Science and Decision Analytics program leave with a genuinely distinctive combination of capabilities that are difficult to find in a single individual, and that combination is precisely what employers are searching for.
On the technical side, they will have hands-on proficiency with Python and R; machine learning engineering and MLOps practices; data pipeline architecture in cloud environments using tools like Apache Spark and MongoDB Atlas; statistical modeling and causal inference; time series forecasting; and business intelligence through platforms like Tableau and Power BI. They will also have deep experience with generative AI, large language model evaluation, prompt engineering, and responsible GenAI deployment.
On the strategic and ethical side, they will be equipped to conduct AI bias and fairness audits, apply global governance frameworks, design data ethics policies, integrate ESG and sustainability metrics into data system design, and communicate complex analytical findings clearly to executive and non-technical audiences.
Crucially, they will know how to work across disciplines. The program's capstone experience, its peer collaboration model, and its case-based learning approach all build the cross-functional, team-oriented mindset that real organizations need. The skills that make our graduates competitive aren't just the technical ones — it's the ability to connect data science to decision-making, to understand the ethical stakes of a model before it's deployed, and to lead with both rigor and responsibility.
“Graduates leave with a genuinely distinctive combination of capabilities that are difficult to find in a single individual, and that combination is precisely what employers are searching for.”
What career paths could graduates of Brandeis Online’s MS in Applied Data Science and Decision Analytics pursue?
The career pathways are genuinely broad, which reflects how pervasive the need for data fluency has become across industries.
Graduates are well-positioned for roles like Data Scientist, Machine Learning Engineer, Analytics Manager, Business Intelligence Developer, Data Engineer, AI Product Manager, AI Governance Analyst, Chief Data Officer, Director of Data Strategy, and Decision Intelligence Consultant. Those who complete the program with a focus on governance and ethics are particularly well-positioned for the growing category of roles such as Data Ethics Officer, Chief Trust Officer, and Director of Responsible AI, that organizations are standing up in response to regulatory pressure from frameworks like the EU AI Act and NIST AI RMF.
In terms of industries, graduates are competitive in healthcare, financial services, technology, consulting, public sector, life sciences, and higher education. The Boston ecosystem in particular, home to major employers like CVS Health, Deloitte, Amazon, and leading pharmaceutical and research hospitals, offers a strong opportunity for program graduates who want to stay regional. And for those who want a national or global scope, the skills in this program travel well.
What types of students would do well in Brandeis Online’s Applied Data Science program?
I think about this in terms of drive more than background. You don't need to come in as a programmer or a statistician; though, if you are, you'll find plenty of challenge and growth. What you do need is genuine curiosity about data, comfort with ambiguity, and a real desire to connect analytical work to meaningful decisions.
The ideal student for this program is someone who is analytically oriented, professionally ambitious, and motivated by real-world impact. If you see data as a tool for making better decisions, not just generating reports, this program was built for you.
“If you see data as a tool for making better decisions, not just generating reports, this program was built for you.”
What are you most looking forward to about this program?
The community. I know that might sound like a cliché answer, but I mean it in a very specific way. This program draws people from remarkably different backgrounds: mid-career professionals in healthcare or finance who want to level up their analytics capabilities, cloud engineers who want to add depth in governance, policy researchers who want to extend their analytical impact, and compliance managers who want to lead AI ethics initiatives. When you put those people in a room together, even in a virtual asynchronous room, something remarkable happens. They challenge each other's assumptions. They bring domain knowledge that enriches the coursework in ways that no textbook could.
I'm also genuinely excited about what it means for students to build skills right now. We're at an inflection point in AI adoption, and the professionals who graduate from this program over the next two to three years will step into roles that genuinely need their expertise. That's a rare feeling in education, the sense that you're preparing people for something that is already here, urgently needed, and growing.
“We're at an inflection point in AI adoption, and the professionals who graduate from this program over the next two to three years will step into roles that genuinely need their expertise.”
The world doesn't need more data; it needs more people who know how to use it wisely. If you're ready to build the technical skills, the ethical judgment, and the strategic fluency to lead in an AI-powered world, I'd love to have you in this program.
Learn more about the Master of Science in Applied Data Science and Decision Analytics at Brandeis Online, and take the first step toward becoming the kind of data professional that organizations everywhere are searching for.