# Two Sigma Engineering Published articles for Two Sigma Engineering. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## 5 Career Myths From Women in Engineering DevFeed: [5 Career Myths From Women in Engineering]() Original publisher: [Read original article]() Author: Emily Majewski Published: 2026-03-17T13:28:39Z Content type: opinion Language: en Sources: [Two Sigma Engineering]() Topics: [Job](), [Software Engineering](), [engineering-culture](), [Amazon Web Services](), [Feature Engineering](), [Finance](), [Users]() Tags: [advice](), [career](), [careers](), [engineering](), [skills](), [software-engineer](), [team](), [users]() ### AI overview The article examines five common career myths through the experiences of three Two Sigma engineering leaders. Their nonlinear careers illustrate how lateral moves, detours, and varied roles can build useful skills and inform later work in software engineering, architecture, and technical leadership. ### Source excerpt The post 5 Career Myths From Women in Engineering appeared first on Two Sigma. ## AI in Investment Management: 2026 Outlook (Part II) DevFeed: [AI in Investment Management: 2026 Outlook (Part II)]() Original publisher: [Read original article]() Author: Emily Majewski Published: 2026-01-21T15:55:26Z Content type: opinion Language: en Sources: [Two Sigma Engineering]() Topics: [Artificial Intelligence](), [AI Models](), [LLMs](), [scaling](), [Compression]() Tags: [2026](), [ai](), [frontier-ai](), [llms](), [models]() ### AI overview Two Sigma leaders discuss how AI may change quantitative investment management, emphasizing productivity improvements, workflow integration, and the use of internal context. The article also highlights a shift toward efficiency, specialized architectures, neural compression, and improved model interpretability. ### Source excerpt The post AI in Investment Management: 2026 Outlook (Part II) appeared first on Two Sigma. ## AI in Investment Management: 2026 Outlook (Part I) DevFeed: [AI in Investment Management: 2026 Outlook (Part I)]() Original publisher: [Read original article]() Author: Emily Majewski Published: 2026-01-12T17:05:01Z Content type: opinion Language: en Sources: [Two Sigma Engineering]() Topics: [Artificial Intelligence](), [AI Strategy](), [AI Development]() Tags: [2026](), [agentic-ai](), [ai]() ### AI overview Two Sigma leaders, engineers, and researchers discuss how AI may affect quantitative investment management in 2026 and beyond. They highlight productivity gains alongside new challenges, the continuing importance of human judgment, and the value of integrating governed AI tools across organizational workflows. ### Source excerpt The post AI in Investment Management: 2026 Outlook (Part I) appeared first on Two Sigma. ## Treating Data as Code at Two Sigma DevFeed: [Treating Data as Code at Two Sigma]() Original publisher: [Read original article]() Author: Emily Majewski Published: 2025-11-13T16:09:02Z Content type: article Language: en Sources: [Two Sigma Engineering]() Topics: [data-engineering](), [Data Management](), [Code](), [CI/CD](), [Terraform](), [Testing]() Tags: [ci-cd](), [code](), [data](), [data-engineering](), [deployment](), [infrastructure-as-code](), [quality]() ### AI overview This article explains Two Sigma's approach to treating data as code. It describes applying software development practices such as version control, automated testing, reproducibility, infrastructure as code, and CI/CD to data management, including the use of Terraform and dbt. ### Source excerpt The post Treating Data as Code at Two Sigma appeared first on Two Sigma. ## Platform Thinking: Three Views from Two Sigma Leaders DevFeed: [Platform Thinking: Three Views from Two Sigma Leaders]() Original publisher: [Read original article]() Author: Emily Majewski Published: 2025-10-23T14:49:45Z Content type: article Language: en Sources: [Two Sigma Engineering]() Topics: [data-engineering](), [data](), [Large Language Model](), [Development](), [Feature Engineering](), [Artificial Intelligence](), [BigQuery](), [CI/CD](), [AI research agents](), [Open Source Models & Datasets]() Tags: [ai](), [ai-agents](), [bigquery](), [ci-cd](), [data](), [data-engineering](), [datasets](), [feature-engineering](), [llms](), [open-source](), [platform](), [post]() ### AI overview Two Sigma leaders describe the company's platform-oriented approach to data, technology, and management. The article highlights parallel delivery of raw and curated datasets, BigQuery and CI/CD practices, reusable data contracts, LLM-assisted feature engineering, controls for temporal leakage, and possible uses of multiple AI agents in quantitative research. ### Source excerpt The post Platform Thinking: Three Views from Two Sigma Leaders appeared first on Two Sigma. ## Odysseus to AI: Matt Greenwood on the Dev Interrupted Podcast DevFeed: [Odysseus to AI: Matt Greenwood on the Dev Interrupted Podcast]() Original publisher: [Read original article]() Author: Emily Majewski Published: 2025-05-27T16:55:02Z Content type: opinion Language: en Sources: [Two Sigma Engineering]() Topics: [Artificial Intelligence](), [engineering-culture](), [AI Inference](), [Development](), [Large Language Model](), [Machine learning]() Tags: [agentic](), [ai](), [culture](), [dev](), [engineering-culture](), [llms](), [machine-learning](), [podcast]() ### AI overview A Dev Interrupted podcast discussion with Two Sigma Chief Innovation Officer Matt Greenwood explores AI advisory agents, intentional innovation, engineering culture, and the use of LLMs and other AI approaches in systematic investment processes. Greenwood describes an "epsilon and omega" approach of iterative steps toward long-term goals and an advisory, oracle, and operational framework for AI applications. ### Source excerpt The post Odysseus to AI: Matt Greenwood on the Dev Interrupted Podcast appeared first on Two Sigma. ## AI Core Team Lead Mike Schuster on How to Get the Most From LLMs DevFeed: [AI Core Team Lead Mike Schuster on How to Get the Most From LLMs]() Original publisher: [Read original article]() Author: Joy Looney Published: 2025-02-04T17:03:42Z Content type: opinion Language: en Sources: [Two Sigma Engineering]() Topics: [LLMs](), [Artificial Intelligence](), [Generative AI](), [Natural language processing](), [Prompt Engineering](), [data](), [Programming]() Tags: [ai](), [data](), [generative-ai](), [llms](), [programming]() ### AI overview Two Sigma AI Core Team Lead Mike Schuster discusses practical uses and limitations of large language models. He emphasizes measuring their value through current use cases, including faster data processing, model training, experimentation, productivity improvements, and feature extraction from financial text. ### Source excerpt The post AI Core Team Lead Mike Schuster on How to Get the Most From LLMs appeared first on Two Sigma. ## Improving Compute Sustainability: A Case Study DevFeed: [Improving Compute Sustainability: A Case Study]() Original publisher: [Read original article]() Author: Emily Majewski Published: 2024-10-07T20:45:28Z Content type: article Language: en Sources: [Two Sigma Engineering]() Topics: [Green Software](), [Computing](), [cpu](), [Hardware](), [Software]() Tags: [case-study](), [compute](), [computing](), [cpu](), [efficiency](), [emissions](), [energy](), [hardware](), [software](), [sustainability]() ### AI overview Two Sigma describes a sustainability program examining how to improve the efficiency of its compute resources. A case study focuses on using a routine server refresh to reconfigure resources, increase server utilization, reduce hardware, and lower power consumption while maintaining performance. ### Source excerpt The post Improving Compute Sustainability: A Case Study appeared first on Two Sigma. ## Office Hours with Engineering Managing Director Mae Santos DevFeed: [Office Hours with Engineering Managing Director Mae Santos]() Original publisher: [Read original article]() Author: Emily Majewski Published: 2024-06-26T17:34:49Z Content type: article Language: en Sources: [Two Sigma Engineering]() Topics: [reliability](), [systems](), [Data pipelines](), [Resilience](), [Automation]() Tags: [automation](), [best-practices](), [collaboration](), [data-pipelines](), [engineering](), [integrity](), [reliability-engineering]() ### AI overview In this Office Hours interview, Two Sigma engineering leader Mae Santos discusses her career, leadership values, and responsibilities overseeing critical applications and data reliability engineering. She emphasizes integrity, collaboration, resilience, and designing reliability into applications and data systems from the beginning. ### Source excerpt The post Office Hours with Engineering Managing Director Mae Santos appeared first on Two Sigma. ## NeurIPS 2023: Our Favorite Papers on LLMs, Statistical Learning, and More DevFeed: [NeurIPS 2023: Our Favorite Papers on LLMs, Statistical Learning, and More]() Original publisher: [Read original article]() Author: Emily Majewski Published: 2024-03-21T19:52:06Z Content type: article Language: en Sources: [Two Sigma Engineering]() Topics: [NeurIPS](), [machine learning research](), [LLMs](), [LLM evaluation / benchmarking](), [Machine learning]() Tags: [evaluation](), [llms](), [machine-learning-research](), [neurips](), [papers]() ### AI overview Two Sigma reviews selected papers and presentations from NeurIPS 2023, with particular attention to large language models and statistical learning. It discusses research arguing that some apparent emergent abilities in LLMs may result from nonlinear metrics, limited evaluation resolution, and insufficient sampling. ### Source excerpt The post NeurIPS 2023: Our Favorite Papers on LLMs, Statistical Learning, and More appeared first on Two Sigma.