Institutional Sales Intern

M Science; New York (NY); On-site; USD 2,066,000 - 3,444,000; Part time

Job summary

M Science is seeking a Summer 2027 Institutional Sales Intern in New York, NY to support outreach, tailor client presentations, and collaborate with sales, product, and analyst teams. You will engage with institutional investors, help demonstrate data-driven insights, and contribute to client conversations and onboarding activities.

This hands-on, client-facing internship offers exposure to data science in finance, AI tools, and an active investment technology platform, with a 10–12 week

Qualifications

• Pursuing a bachelor’s degree in Business, Finance, Economics, Data Science, or related field anticipated to graduate between December 2027 and May 2028.
• Interest in financial markets, data products, AI, and client‑facing work.
• Curiosity about how different investors use data to make decisions.
• Strong organization, attention to detail, and willingness to take ownership of work.
• Ability to collaborate across sales, product, and analyst teams.
• Excellent communication skills, a strong work ethic, and a desire to learn and grow in a fast‑paced environment.
• Working knowledge of Claude, ChatGPT, Excel, PowerPoint, and Outlook.
• Experience with a CRM, financial data, or other AI tools is helpful, but not required.

Responsibilities

• Research prospective hedge fund and asset management clients, including their investment strategies and data workflows.
• Tailor outreach and presentations to portfolio managers, investment analysts, data science teams, and technology leaders.
• Identify relevant datasets, data trends, and use cases addressing client questions.
• Build clear examples of how clients can use M Science’s data-driven research, Unified Data Model, and MCP Server.
• Join client meetings and calls, capture feedback, and help coordinate follow-up.
• Track client activity and product engagement in our CRM.
• Support account teams with onboarding, adoption, renewals, and opportunities to expand usage.
• Work with product and analyst teams to bring client questions and workflow needs back into the business.

Skills

Attention to detail

Communication skills

Team collaboration

Ownership mindset

Curiosity

Education

Bachelor’s degree in Business, Finance, Economics, Data Science, or related field

Tools

CRM

Excel

PowerPoint

Outlook

Job description

Summer 2027 Institutional Sales Intern – Hedge Funds & Asset Managers

Location: New York, NY | On-site

Program Duration: Summer 2027 (10-12 Weeks) (30 hr per week commitment)

Looking for applicants anticipated to graduate between December 2027 and May 2028

About M Science

M Science helps institutional investors see what is changing across businesses, industries, and consumer behavior—and understand why it matters. Our team turns differentiated data into intelligence that helps investors find signals, monitor investment ideas, and build conviction. M Science gives clients the flexibility to use that intelligence in the way that fits their process: read our research, explore the underlying data through our Unified Data Model, or bring it into AI tools and internal systems through our MCP Server.

The Opportunity

We are seeking an Institutional Sales Intern to join our team for the summer. You will work with sales, product, and analyst teams to help institutional investors understand what M Science data and intelligence can reveal and how to leverage it across their investment process.

You will support outreach and client conversations, develop examples tailored to different investor needs, and help drive engagement with across our product suite. This is a hands‑on, client‑facing role for someone interested in markets, data, AI, and how investment teams actually work.

Key Responsibilities

• Research prospective hedge fund and asset management clients, including their investment strategies, areas of coverage, and data workflows.
• Help tailor outreach and presentations to portfolio managers, investment analysts, data science teams, and technology leaders.
• Identify relevant datasets, data trends, and use cases that address specific client questions.
• Build clear examples of how clients can use M Science’s data-driven research, Unified Data Model, and MCP Server to explore underlying data, compare companies, identify inflections, and validate signals.
• Join client meetings and calls, capture feedback, and help coordinate follow‑up.
• Track client activity and product engagement in our CRM.
• Support account teams with onboarding, adoption, renewals, and opportunities to expand usage.
• Work with product and analyst teams to bring client questions and workflow needs back into the business.

What You’ll Learn

• How portfolio managers use data to develop ideas, monitor positions, and build conviction.
• How fundamental analysts investigate company trends, compare peers, and test a thesis against the underlying data.
• How quantitative and data science teams evaluate datasets, build repeatable signals, and incorporate new inputs into their models.
• How technology and AI teams bring external intelligence into internal tools and investment workflows, including through our Unified Data Model and MCP Server.
• How these teams work together—and how to make M Science useful to each of them.

Preferred Qualifications

• Pursuing a bachelor’s degree in Business, Finance, Economics, Data Science, or a related field anticipated to graduate between December 2027 and May 2028
• Interest in financial markets, data products, AI, and client‑facing work.
• Curiosity about how different investors use data to make decisions.
• Strong organization, attention to detail, and willingness to take ownership of work.
• Ability to collaborate across sales, product, and analyst teams.
• Excellent communication skills, a strong work ethic, and a desire to learn and grow in a fast‑paced environment.
• Working knowledge of Claude, ChatGPT, Excel, PowerPoint, and Outlook.
• Experience with a CRM, financial data, or other AI tools is helpful, but not required.

Why M Science?

You’ll work directly with teams bringing differentiated data and intelligence into the modern investment workflow. You’ll learn how to speak to different clients, translate their questions into useful data applications, and help them turn signals into greater investment conviction.