Lead Reasoning & Decision Optimization Scientist

Kindredventures; San Francisco (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Kindredventures is building a Large Physics foundation Model focused on causal intelligence to predict and influence the future in real-world environments. The role targets researchers who define objectives and evaluation methods for decision models in high-stakes settings.

We seek experts in operations research and decision science with PhD-level or equivalent background who can translate operational realities into rigorous optimization problems and collaborate across ML and product teams to

Qualifications

• PhD or equivalent experience in operations research, decision science, or related field.
• Strong understanding of optimization and decision-making under uncertainty.
• Experience in high-stakes operational settings where forecasts drive decisions.
• Ability to evaluate optimization/decision models, not only build them.
• Ability to collaborate with ML researchers and translate realities into technical problems.

Responsibilities

• Formulate objectives, constraints, and decision problems for reasoning models.
• Develop methodology for evaluating decision quality under uncertainty, including counterfactuals.
• Translate complex operational realities into well-posed optimization problems.
• Provide rigor in validation of optimization and decision-making models for real-world use.
• Partner with reasoning, evaluation, and product teams to connect research to decisions.

Skills

Operations research

Decision science

Optimization under uncertainty

Stochastic methods

High-stakes forecasting

Model evaluation

Collaboration with ML researchers

Education

PhD or equivalent experience

Job description

Kindredventures is building a Large Physics foundation Model focused on causal intelligence to predict and influence the future in real-world environments. The role targets researchers who define objectives and evaluation methods for decision models in high-stakes settings.

We seek experts in operations research and decision science with PhD-level or equivalent background who can translate operational realities into rigorous optimization problems and collaborate across ML and product teams to