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About the Role
Gen AI Lead / Data Scientist (PhD) – Prospect 33 (P33.ai)
Employment Type: Full-Time
Work Model: In-House Leadership Role
About Prospect 33
Prospect 33 is expanding its Data, AI & Research Technology (DART) practice. This is not a vendor or staffing role. You will be a core, in-house member of Prospect 33, owning AI architecture and delivery end-to-end while leading high-impact initiatives for some of the world’s most sophisticated banks and asset managers.
You will sit at the heart of the firm, helping define how generative and predictive AI transform investment research, sales, trading, and risk across global capital markets.
What You’ll Do
- Lead the design, development, and productionization of next-generation Generative AI systems and data-driven models.
- Architect and own end-to-end AI/ML pipelines, from data ingestion and feature engineering to model training and low-latency inference.
- Drive advanced GenAI initiatives including LLM-based systems, RAG pipelines, and agentic AI frameworks.
- Provide technical leadership across distributed systems, optimizing Spark and Databricks workloads for performance, latency, and cost.
- Establish best practices for MLOps and LLMOps including CI/CD, infrastructure-as-code, experiment tracking, and monitoring.
- Mentor engineers and data scientists and serve as a senior technical representative with internal leadership and external stakeholders.
Must-Have Qualifications
- PhD in Computer Science, Machine Learning, Artificial Intelligence, Engineering, or a closely related field.
- Expert-level proficiency in Python, SQL, PySpark, and modern ML frameworks in production environments.
- Deep understanding of algorithms, data structures, distributed systems, and large-scale model training.
- Proven track record of translating research into production-grade AI or ML systems.
- Strong foundation in statistical modeling, machine learning theory, and applied AI system design.
Strong Advantages
- Hands-on experience with Generative AI including LLMs, RAG architectures, agent frameworks, and prompt engineering.
- Experience with Databricks, Snowflake, Kubernetes, Terraform, and cloud-native AI platforms.
- Exposure to capital markets including investment research, trading, risk, or alternative data.
- Experience operationalizing advanced research into scalable enterprise systems.
Why Prospect 33
- True ownership and impact as a core, in-house leader.
- Direct collaboration with leading global financial institutions.
- Opportunity to shape the firm’s GenAI strategy and intellectual property.
- Recognized culture of technical excellence and innovation.
Job Type: Full-time
Pay: $120,000.00-$200,000.00 per year
Work Location: In person
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