Chinmoy Mohapatra — Mentor profile, Title: Senior Research Scientist, Company: Amazon, Industry: Supply Chain | Data Analytics | Technology | E-Commerce, Mentor Type: Albers

Background

Job Description

I lead the design and deployment of large-scale optimization and forecasting systems for Amazon's global Last Mile delivery network. My work combines operations research, machine learning, and systems architecture to solve interconnected planning problems — determining which packages go where, how much delivery capacity to allocate, and when to adjust plans in real time. I manage forecasting systems that generate over one million concurrent predictions across six global regions and optimization engines that process routing decisions for more than 30 million packages daily. I also mentor research and data scientists across multiple teams and represent Amazon at international scientific conferences.

Company Description

Amazon is a global technology and e-commerce company that operates one of the world's largest logistics and supply chain networks, delivering billions of packages annually to customers across more than 100 countries. Its Last Mile delivery operation alone spans over 1,000 delivery stations across the United States, Europe, Japan, India, the Middle East, and emerging markets.

Employment History

Amazon - 9 years

Education

PhD, Supply Chain and Operations Management, University of Texas at Austin (McCombs School of Business)

No civic involvement entered

Mentoring Objectives & Scope

I want students to leave our time together with two things: clarity on how to think about their career as a series of compounding decisions, and practical tools to navigate the transition from academic problem-solving to professional impact.

My background spans operations research, machine learning, and large-scale systems — I've built optimization and forecasting systems at Amazon and BNSF Railway that process millions of decisions daily. But the skills that got me here weren't just technical. Learning how to frame a problem for a non-technical audience, how to influence without authority, how to write clearly, how to choose which problems to work on — these are the skills that separate someone who does good work from someone whose work changes how an organization operates.

I'm particularly well-suited to mentor students interested in analytics, data science, operations research, supply chain, or applied machine learning — but I also enjoy working with students who are figuring out what they want to do and need a sounding board. I've navigated a PhD to industry transition, moved between industries (railroad to tech), and built a career at the intersection of research and practice, so I understand the uncertainty that comes with those pivots.

My approach is conversational and student-driven. I'll ask a lot of questions to understand where you are and where you want to go, and then I'll be direct about what I think will help. I'm not going to assign homework, but I will push you to think rigorously about your choices — the same way I'd approach an optimization problem. I'm also happy to do hands-on work like resume reviews, mock interviews, or talking through how to position yourself for a specific role.

As a mentor, I can support students in the following: 

- Resume review, interview prep, LinkedIn branding
- Career exploration, matching interests and talents with professions and industries
- Student transition from college to first professional role
- Building technical or subject matter expertise (hard skills)
- Improved communication and interpersonal skills
- Development of leadership skills, confidence, and executive presence
- Expanding a network, building connection, navigating an organization
- Helping entrepreneurial students define a business or product and business plan
- Career Pivot - transition to new role, career, and industry

When and where do you hold meetings with your students?

Hybrid (mix of in-person and virtual) Bellevue or Seattle, WA — happy to meet at a coffee shop near campus or downtown.

Additional Information

My career has been built at the intersection of mathematical optimization, machine learning, and real-world decision systems. Before Amazon, I built train routing and scheduling optimization at BNSF Railway, where our operations research work contributed to the INFORMS Prize — the highest honor in the practice of operations research. I hold two granted U.S. patents and have eight additional filings pending. I'm passionate about mentoring because I believe the most impactful work happens when rigorous analytical thinking meets practical problem-solving, and I enjoy helping students bridge that gap. I'm also active in the research community as an Area Chair for NeurIPS, a reviewer for several leading journals, and a member of the INFORMS Gaver Early Career Award Committee.