Balyasny Asset Management (BAM) operates at the intersection of finance and technology. Our world-class platform brings together portfolio managers, financial analysts, quantitative researchers, and software engineers who work together to identify investment opportunities and generate lasting returns for our investors. BAM's Equities Data Science & AI (DSAI) team is a group of data scientists, engineers, and researchers who deliver data- and AI-driven insights to BAM's equities portfolio managers.
We are seeking an exceptional Senior Data Scientist to join our team focused on the large and high-growth TMT equities sector. In this role, you will collaborate directly with portfolio managers to design and deliver data-driven solutions that address the most critical TMT investment debates and build custom AI workflows that accelerate and enhance the investment process, expanding research breadth and depth while increasing speed to insight.
What You'll Do
- Partner with Portfolio Managers: Identify and frame key investment debates in the TMT equities sector, and design and conduct data-driven research to address them with rigorous critical thinking and clear investment relevance.
- Enable with AI: Partner with portfolio managers to apply BAM's industry-leading AI platform to custom agentic solutions that enhance their investment process and accelerate the breadth, depth, and speed of research insight.
- Forecast the Future: Use advanced mathematical and computational techniques to create predictions with high accuracy and low latency, while applying judgment to evaluate model limitations, data quality, and decision usefulness.
- Build & Scale Data Products: Lead the development of data products and scale solutions that empower the sector's equities investment teams and drive alpha generation.
- Shape Sector Strategy: Contribute to the development and execution of sector-level data strategies, driving engagement and adoption of the team's product across the TMT equities franchise.
- Innovate with Investment Staff: Brainstorm creative applications of data and AI in the investment process, pushing the boundaries of what's possible while maintaining a high bar for analytical rigor and practical impact.
What We're Looking For
- Alpha-First Mindset: A passion for delivering value to investment teams by questioning the consensus and looking for informational advantages in data, combined with the critical-thinking skills to assess ambiguous questions, challenge assumptions, and form clear, defensible conclusions.
- Technical Mastery: Solid command of statistics, analytics, and machine learning, with a proven track record of informing investment or business decisions. Familiarity with large-scale alternative dataset management processes, including panelization, mapping, tagging, and other relevant areas of data science.
- Sector Expertise: Knowledge of the TMT investing space and direct experience working with key sector datasets, with equities investment experience strongly preferred.
- Proven Experience: 7+ years in data science, data analytics, or a related field.
- Educational Background: BS or MS in Mathematics, Finance/Economics, Computer Science, Statistics, Engineering, or Technology.
- Crisp Presentation & Communication: Ability to distill complex technical concepts to non-technical audiences. Motivation to understand and integrate both up- and downstream processes.
- AI Applications: Practical experience harnessing LLMs and prompt engineering, coding agents, and multi-step workflow build-outs to improve research breadth, analytical depth, and speed to insight.
- Coding: Python, Snowflake/SQL, and Git, with a working proficiency with Linux command-line tools and environments. Familiarity with software engineering design principles is a plus.
Join BAM's Equities Data Science & AI team and help shape the future of data-driven equities investing. If you're passionate about leveraging data and AI to solve complex problems, increase the breadth, depth, and speed of investment insight, and drive investment performance, we want to meet you.