$98K+
Avg. year-1 total comp · US jobs
#3 Full-Time, In-Person MSBA
Tech Guide 2026
STEM-Designated
Eligible for 3 years of OPT
9 · 12 · 16 month tracks
Flexible for your goals
~100 Students per Cohort
Individual guidance & mentorship
Why MS in Business Analytics at Questrom
A program built around who you’re becoming, not just what you’re learning
“The Questrom MSBA is a brilliant and intense program for those who enjoy getting into the weeds. The program is rigorous and so relevant to the industry that I’m already using multiple skills I developed during the program in my current role.”
Before
Data analyst | technically strong | unsure of next step
After Questrom
Senior Product Manager, Digital Product · CVS Health
Where MSBA graduates work
Select employers
McKinsey & Company
Dell
Blackrock
Cigna
NBC Universal
Deloitte
Fidelity
AstraZeneca
Our MSBA model
Developing the professionals
companies actually need
Every MSBA teaches analytics. Questrom is organized around a different model — one where knowledge only matters if it becomes capability. Four pillars drive that.
Where you end up
From where you started — to where you’re going
The best signal of a program isn’t where graduates land on day one. It’s where they are three years later. Here are three alumni who came in with different backgrounds and left on very different trajectories.
A journey to who you’ll become
Most programs offer career services. Questrom offers a structured professional formation journey — beginning day one and running through your first offer. Click any stage to explore.
Assess
Strengths
Start with self-knowledge
Before you can build toward something, you need to know where you’re starting from. In your first weeks, you complete a structured strengths assessment with your dedicated career advisor — identifying what you’re already good at, what employers in your target sectors want, and the specific gaps to close.
- Strengths inventory — formal assessment with advisor debrief
- Industry target mapping — where you want to go and what’s realistic
- Gap analysis — a concrete development plan for the year ahead
- 1:1 with career advisor — dedicated to your sector, not shared across 300 students
Build
Capabilities
Mentor Match
Matched by industry, function, and goal — not class year. Built-in touchpoints, not left to chance.
- Client projects — real companies, real data, real stakes each semester
- BU Spark! lab — innovation lab with startup and civic clients
- Consulting lab — structured problem-solving with firm mentors
- Case competitions — Sloan, internal analytics competitions, and more
Client
Feedback
Peer Cohort Group
A consistent peer group that gives you another source of feedback, perspective, and support throughout the program.
- In-class practitioner reviews — regular feedback from industry guests
- Client feedback sessions — structured debrief with real project sponsors
- Corporate partner reviews — 12 partners co-invest in student development
- Iterative improvement — feedback loops built into every major deliverable
Balanced
Scorecard
Client Feedback
Clients give you feedback on your communication, judgment, and teamwork — adding a real-world perspective to what you’re learning.
- Analytics capability — technical depth across tools and methods
- Communication & influence — making data mean something to non-technical audiences
- Client & team management — how you show up under real professional conditions
- Professional presence — executive readiness, not just academic readiness
Mentor
Network
Midpoint Reflection
Recalibrate your plan with your coach. What changed? What do the next four months need to be?
- Alumni mentor match — paired by industry, role, and background
- Exec Connect — senior leader access in your target sector
- Faculty networks — real industry relationships, not just academic contacts
- Global alumni community — Questrom MSBA grads across every major analytics market
Offer
& Beyond
Developmental Capstone
Present your professional progress to faculty, your mentor, and a Corporate Partner. Evidence no transcript can provide.
- 96% placed within 6 months — 3-year average
- $98K+ avg. first-year comp — US jobs, 3-year average
- 48% received 2+ offers — more leverage at the negotiating table
- Strong 3–5 year trajectory — tracked and published in annual career report
Phoenix Wang
Data Scientist · Meta
+64% salary lift post-MSBA
↓
Questrom MSBA
↓
Data Analyst → Wayfair
↓
“The client projects taught me to communicate findings to people who cared about the decision, not the model. That skill got me from Wayfair to Meta faster than anything technical would have.”
Connect with Phoenix Wang on LinkedIn
Jacinto Lemarroy
Analytics Consultant · Salesforce
+52% salary lift post-MSBA
↓
Questrom MSBA
↓
Analytics Consultant → Salesforce
“I came in with industry experience but no formal analytics credential. Questrom gave me the technical foundation and the professional context to land a role I never expected.“
Connect with Jacinto Lemarroy on LinkedIn
Michael Webber
Management Consultant · PwC
+71% salary lift post-MSBA
↓
Questrom MSBA
↓
Management Consulting → PwC
“Questrom’s professional development support was unlike anything I expected. My advisor understood what PwC was looking for — not just in skills, but in how I showed up. That coaching made the difference.”
Connect with Michael Webber on LinkedIn
AI Capability
You don’t study AI here.
You collaborate with it.
Most programs added an AI elective. We rebuilt our curriculum around AI as a professional tool. The question isn’t whether your future work involves AI — it’s whether you know how to direct it, evaluate it, and take responsibility for what it produces.
AI in your workflow
AI isn’t a subject. It’s how you collaborate.
From day one, you’re using LLMs, Copilot-style tools, and AI-augmented analytics platforms — embedded in real project work, not a dedicated AI class. You’ll learn when to trust the output, when to challenge it, and how to frame prompts to get analytically sound results.
What this looks like in practice
In a client project for a Boston retailer, your team uses LLM-assisted data synthesis to surface customer sentiment patterns, then validates the model’s output against your own statistical analysis. The client gets a faster insight loop. You learn how to be the human in that loop — and why that matters.
AI tools across your curriculum
- Large Language Models | Used across 6+ courses
- GenAI for analytics pipelines | Core methods course
- Neural networks & deep learning | Data & Methods concentration
- AI-augmented decision support | Client project standard
Methods & tools
Technical depth with professional judgment
You’ll graduate knowing how to build with AI and how to critique it. Supervised and unsupervised learning, neural networks, NLP, and GenAI pipelines are in your toolkit — along with the statistical and business judgment to know when the model is wrong or misleading.
Sample methods you’ll work with
Regression · Classification · Clustering · Neural networks · LLMs · Prompt engineering · NLP pipelines · Causal inference · A/B testing design · Reinforcement learning (intro)
Tools you’ll actually use
Python, R, SQL, PyTorch, scikit-learn, Snowflake, Tableau, OpenAI API, Spark, dbt
Responsible AI
Who’s responsible when the model is wrong?
You are. Responsible AI isn’t a checkbox module — it’s woven into every project that uses AI output. You’ll learn to audit for bias, document model limitations, and communicate uncertainty to non-technical stakeholders who will make real decisions on your analysis.
What responsible AI looks like in project work
Every AI-assisted client deliverable includes a “model limitations” section — explaining where the model’s confidence degrades, what assumptions it makes, and what a human reviewer should double-check before acting on the output.
What you’ll be able to do
- Audit AI outputs for bias and distributional shift
- Communicate model uncertainty to non-technical stakeholders
- Design governance frameworks for AI-driven decisions
- Comply with emerging AI regulations in healthcare, finance, and public sector
vs. other programs
Learning about AI vs. learning with it
At most MSBA programs, AI appears in one or two dedicated courses. At Questrom, it appears in how you do your work — and that changes what you’re capable of by graduation.
COMPARING THE APPROACHES
Most programs
One dedicated AI/ML elective. Projects use pre-cleaned datasets. AI tools are for assignments, not professional formation.
Questrom MSBA
AI embedded in core courses and client projects. Real-world data. You direct the AI, evaluate its output, and own the result.
Upcoming Admissions Events
Attend an event and apply for free. Join us to discover program insights and enjoy a waived application fee when you apply to a Questrom graduate degree program.
Your data career starts in Boston
Join a cohort that looks like the real world — engineers, business graduates, scientists, and humanists, all learning to lead through data. Applications are reviewed on a rolling basis.
All applicants are automatically considered for merit scholarships — no separate application required. Applying in earlier rounds significantly increases your chances of receiving an award.
Application Deadlines
Round 1 | October 13, 2026
Round 2 | November 17, 2026
Round 3 | January 7, 2027
Round 4 | February 16, 2027
Round 5 | March 16, 2027
Round 6 | April 20, 2027