About the Role
The role involves designing and implementing AI models to interpret complex private market datasets, supporting investment decision-making with scalable tools and intelligent systems.
Responsibilities
- Design machine learning models tailored to private equity and venture capital data
- Process unstructured financial documents using natural language understanding techniques
- Collaborate with engineers to integrate AI features into core platforms
- Evaluate data quality and develop pipelines for consistent model training
- Translate investment strategies into algorithmic signals
- Optimize model performance for accuracy and speed
- Monitor deployed systems for reliability and drift
- Work closely with domain experts to refine data labeling
- Develop metrics to assess model impact on investment outcomes
- Stay current with advancements in AI relevant to financial markets
- Document model architecture and decision logic clearly
- Support compliance with data governance standards
- Iterate on feedback from portfolio and deal teams
- Build prototypes for new AI use cases
- Contribute to technical roadmap planning
- Ensure models are interpretable to non-technical stakeholders
- Manage version control for model development
- Assist in sourcing alternative data for training
- Participate in peer code and model reviews
- Scale solutions across different asset classes
Nice to Have
- PhD in a technical or quantitative discipline
- Published research in AI or financial modeling
- Experience with time series forecasting in finance
- Knowledge of private asset valuation methods
- Contributions to open-source machine learning projects
- Experience mentoring junior data scientists
- Familiarity with compliance frameworks for financial AI
- Worked at a startup or small technology team
- Built AI tools for due diligence automation
- Used retrieval-augmented generation in production
Compensation
Competitive salary with equity and performance bonuses
Work Arrangement
Hybrid remote with office options in major US cities
Team
Small, cross-functional team focused on rapid product development
What We Value
- Curiosity about how AI can transform traditional investment processes
- Ownership of projects from concept to deployment
- Clear communication of technical concepts to non-experts
- Ethical considerations in data use and model design
- Continuous learning in a fast-moving domain
Day-to-Day
- Morning sync with engineering and product teams
- Model training and evaluation cycles
- Reviewing new data sources for integration
- Pair programming sessions with ML engineers
- Presenting findings to investment partners
Available for qualified candidates
