Impact Investing Technology
Total Values
Mentors
Daniel Buckman – Founder and CEO
About Us
Total Values is an early-stage venture building the Portfolio Co-Pilot for mission-driven investors: foundations, family offices, DFIs, and institutional allocators who want to align their capital with measurable social and environmental outcomes, not just financial return. The platform maps every holding in a portfolio to peer-reviewed evidence, forecasts impact across 200+ customizable metrics, and runs multi-objective optimization so investors can see the real trade-offs between risk, return, and impact in one place.
The company was founded by Daniel Buckman, who previously led portfolio construction work tied to Prudential’s $500B General Account and is a Tarrson Fellow at the Rustandy Center.
Advisors include senior leaders from Prudential, BCG, Chicago Booth, and the field of impact measurement (TIIP / Columbia). The team is small, fast-moving, and works at the intersection of quantitative finance, causal inference, and impa
Externship Description
The extern will own, end to end, a new AI-powered research and simulation system inside Total Values’ platform. The system has three connected parts:
- Deep research on interventions. An AI workflow that investigates a given social or environmental intervention, pulling from academic literature, implementer data, and field evidence, and produces a structured view of how it works, who it affects, and under what
- Systems mapping and A module that builds a systems map of the problem space, connects to deal-sourcing and grant-sourcing platforms to surface existing opportunities, and brainstorms new intervention candidates the market has not yet priced.
- Impact and financial simulation. A simulation layer that models how different interventions interact inside a portfolio, capturing feedback loops, crowd-in effects, and substitution, and forecasts both impact outcomes and financial return. For example, a workforce-training intervention and an affordable-housing intervention in the same region may reinforce each other: training raises local incomes, which sustains housing affordability outcomes, which in turn keeps training participants stable enough to complete the program. The simulation layer captures those interdependencies rather than scoring each intervention in isolation.
This externship should interest students who want to work at the frontier of AI, systems modeling, and impact finance. If you are excited about using computational tools to help institutional capital achieve more social impact, and you are comfortable building something new in a domain that has no off-the-shelf playbook, this role will give you rare ownership of a live, commercially relevant system that matters to real allocators.
Role of the extern
The extern will function as the lead builder on this workstream, with Daniel as direct mentor. That means scoping the problem, designing the architecture, building the AI and simulation components, testing them against real intervention cases surfaced from Total Values’ design-partner pipeline, and iterating based on what allocators actually need. The extern will not be a support contributor on someone else’s roadmap. They will own this system and ship it.
Specific Objectives
Deliverable. A working version of the intervention-research, systems-mapping, and simulation system, integrated into Total Values’ platform, tested on at least one real allocation decision from a design partner, and documented clearly enough that the team can extend it.
What the extern will learn.
- How to design AI research workflows that produce decision-grade evidence, not just
- How to build systems maps of interconnected social, environmental, and financial dynamics, and represent them computationally.
- How to simulate multi-agent, multi-outcome systems where interventions interact, compete, and compound: Such as how a technical assistant grant empowers an impact fund to deliver on its targets or policy advocacy unlocks a new market to price in positive social externalities.
- Domain fluency in impact investing, catalytic capital, and institutional portfolio
- How early-stage product decisions are actually made when the customer, the data, and the methodology are all being figured out in parallel.
Training. One-on-one mentorship from Daniel throughout the externship, plus direct exposure to Total Values’ advisor network (Chicago Booth faculty, senior institutional investors, impact measurement researchers) as relevant to the work. No formal certification, but the extern will leave with a portfolio-ready piece of work and a defensible point of view on a frontier field.
Structured time commitment. A regular working session with Daniel at a standing time, plus asynchronous collaboration throughout the week. Additional check-ins as the project demands.
Qualifications
Technical.
- Strong computational modeling skills, ideally including experience with systems mapping and simulation of interconnected systems (agent-based models, system dynamics, causal-loop modeling, or equivalent).
- Comfort building with modern AI tooling (LLM-based research workflows, retrieval, orchestration).
- Fluency in Python or a comparable language, and the ability to move from prototype to something other people can use.
Professional qualities (these matter most).
- Comfort working on messy problems with genuine ambiguity and This is a frontier domain; the right answer is rarely obvious and never pre-specified.
- Grit and resilience. This is a tricky problem nobody has attempted before. It is now possible by wiring together AI-based workflows that embed specialized deep research and systems-mapping capabilities, but the path from “possible” to “working” runs through real intellectual and engineering hurdles. The extern needs to stay with the problem.
- Self-starter. The extern will own the system and is expected to get things done through the inevitable hurdles, without needing tasks handed down.
- A real interest in helping institutional capital achieve more social and environmental impact. Technical talent without the mission fit will not produce the work we need.
Background. Open to masters, doctoral, or postdoctoral students. Strong fits include computational social science, operations research, systems engineering, economics, public policy with a quantitative focus, or a technical discipline with a demonstrated interest in social impact. Specific prior experience in impact investing is not required; curiosity and mission alignment are.