Member of Technical Staff - Research, Operations & Decision Science

About the role

In this position, you will play a pivotal role in shaping the objectives that our AI models strive to achieve. Your focus will be on developing methodologies to evaluate the effectiveness of decisions made by these models. By applying principles from operations research and decision science, you will contribute significantly to our overarching mission of Causal intelligence. Your insights will directly impact the assessment and application of our Large Physics foundation Model (LPM) in addressing real-world challenges.

Key facts

What you'll do

• Establish clear objectives, constraints, and decision-making challenges for our reasoning models to ensure they are aligned with practical applications.
• Develop innovative methods to assess the quality of decisions, particularly in scenarios where outcomes are uncertain or speculative.
• Transform intricate operational scenarios into straightforward optimization and decision-making problems that can be effectively addressed.
• Rigorously test our optimization and decision-making models to validate their applicability in real-world contexts.
• Collaborate closely with both research and product teams to ensure that your findings are effectively integrated into the decision-making processes they support.
• Analyze and interpret data to inform and refine decision-making frameworks, ensuring they are robust and reliable.
• Engage in continuous learning and adaptation of methodologies to keep pace with advancements in operations research and decision science.
• Participate in cross-functional teams to foster a collaborative environment that encourages innovative solutions to complex problems.

Requirements

• A deep understanding of operations research, decision science, or a related field, typically evidenced by a PhD or equivalent professional experience.
• Proficiency in optimization techniques and decision-making under uncertainty, including familiarity with stochastic methods.
• Experience in high-stakes operational environments where predictive analytics inform critical decisions.
• Proven track record in evaluating the effectiveness of optimization or decision models, demonstrating a comprehensive understanding of their practical implications.
• Strong communication skills, enabling effective collaboration with machine learning researchers and the ability to translate real-world challenges into technical problems.
• A proactive approach to problem-solving, with the ability to think critically and creatively in dynamic situations.

Nice to have

• Familiarity with counterfactual reasoning and its applications in decision-making processes.
• Experience with programming languages and tools commonly used in data analysis and modeling, such as Python or R.
• Knowledge of machine learning principles and how they intersect with operations research and decision science.
• Previous involvement in projects that required interdisciplinary collaboration, particularly in tech or research environments.

Skills & tools

• Operations Research
• Decision Science
• Optimization Techniques
• Stochastic Methods
• Counterfactual Reasoning
• Data Analysis Tools (e.g., Python, R)

Practical notes

• Specific details regarding compensation and benefits have not been disclosed.
• The position is based in San Francisco, a hub for innovation and technology, providing a vibrant work environment.
• As a full-time role, you will be expected to engage deeply with both the research and operational aspects of the organization, contributing to a culture of excellence and continuous improvement.
• Candidates should be prepared for a collaborative work atmosphere that values diverse perspectives and innovative thinking.
• Opportunities for professional development and growth within the organization are encouraged, fostering an environment where employees can expand their expertise and advance their careers.

This role offers a unique opportunity to be at the forefront of research and decision science, contributing to groundbreaking advancements in AI and Causal intelligence. If you are passionate about applying your knowledge in a practical setting and making a significant impact, we invite you to explore this exciting opportunity with us at Causal.

About the company

Causality is an influence by which one event, process, state, or subject contributes to the production of another event, process, state, or object where the cause is at least partly responsible for the effect, and the effect is at least partly dependent on the cause. The cause of something may also be described as the reason behind the event or process.