Two Sigma

About the Company

Two Sigma is a financial sciences company that combines advanced technology and data science with rigorous human inquiry to solve the toughest challenges in finance. Two Sigma aims to generate alpha for its clients and deliver differentiated solutions in investment management, securities, private equity, real estate, venture capital, portfolio analytics, and insurance. Founded in 2001 by David Siegel and John Overdeck, Two Sigma employs over ~1,700 curious minds, and is headquartered in New York with offices around the globe. For more information visit www.twosigma.com.

Two Sigma is proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.

The information presented in this profile is offered for recruiting purposes only and should not be used for any other purpose. As such, Two Sigma’s use of LinkedIn is not an offer to, or solicitation of, any potential clients or investors for the provision by Two Sigma of investment management, advisory or any other related services. No information posted by Two Sigma should be construed as investment advice, or as an offer to sell, or a solicitation of an offer to buy, any security or other instrument. All trademarks, logos, information and photos are ®/TM/© Two Sigma Investments, LP or its affiliates. All rights reserved.

Listed Jobs

Company Name

Two Sigma

Job Title

AI Research Scientist - Internship [2026 Summer]

Job Description

Job Title: AI Research Scientist – Internship (Summer 2026) Role Summary: Conduct machine‑learning research focused on financial data, leveraging deep learning, large‑language‑models, and reinforcement learning. Develop and evaluate techniques under guidance of senior researchers, contributing to understanding of noisy, complex economic systems. Expectations: - Masterful use of Python and familiarity with Rust/Java. - Proficiency in TensorFlow and/or PyTorch. - Experience with large‑scale data pipelines for machine‑learning workloads. - Prior engagement in deep learning/LLM/ RL projects, preferably with internship or academic work. - Ability to design, run, and interpret experiments and discuss findings. - Basic statistical knowledge and cloud‑compute, multi‑node operational skills. - Curiosity for financial data science and collaborative research. Key Responsibilities: - Develop novel techniques or infrastructure for a selected research project over ~10 weeks. - Design and implement data pipelines to ingest and process noisy financial data. - Build, train, and fine‑tune deep‑learning models (e.g., transformer‑based LLMs, RL agents). - Conduct rigorous experiments, analyze results, and iterate on modeling strategies. - Collaborate with team members to review research, give/receive feedback, and report progress. - Document methodology and findings for internal use and potential publication. Required Skills: - Python programming (advanced). - Deep‑learning frameworks: TensorFlow and/or PyTorch. - Experience in data‑engineering for ML (ETL, batch/stream pipelines). - Familiarity with cloud platforms (AWS, GCP, Azure) and distributed training. - Statistics fundamentals (probability, inference, hypothesis testing). - Strong analytical and problem‑solving abilities. - Excellent communication and teamwork in a research setting. Required Education & Certifications: - Master’s or Ph.D. candidate in Computer Science, Engineering, or related STEM discipline, penultimate year of study. - Evidence of prior internships, coursework, or projects involving deep learning, LLMs, or reinforcement learning. - Preferred: Publications or research work accepted at top ML conferences (NeurIPS, ICML, ICLR, etc.).

New york, United states

Hybrid

12-11-2025

Company Name

Two Sigma

Job Title

Quantitative Software Engineer: Techniques Engineering

Job Description

**Job Title** Quantitative Software Engineer – Techniques Engineering **Role Summary** Deploy and scale cutting‑edge machine learning research into robust, production‑ready systems. Partner with ML researchers, data teams, and platform engineers to build automated training pipelines, model serving infrastructure, and continuous integration pipelines that deliver high‑performance models to portfolio managers. **Expectations** - Translate experimental prototypes into reusable, maintainable code. - Optimize models for latency, throughput, and resource efficiency. - Maintain highest code quality standards (testing, CI/CD, version control). - Mentor junior engineers and influence technical strategy across functions. **Key Responsibilities** - Collaborate with researchers to evaluate model architectures, training methods, and experimental objectives. - Prototype, refactor, and prod‑grade ML solutions, ensuring scalable and maintainable codebases. - Design, implement, and optimize fully automated training pipelines and evaluation workflows. - Employ model optimization techniques (quantization, distillation, batching) for production deployment. - Continuously monitor, debug, and fine‑tune research and production workflows using automated monitoring and user feedback loops. - Identify bottlenecks, propose process improvements, and implement automation to increase developer and modeler efficiency. - Stay current with emerging ML technologies and integrate advanced methodologies into production systems. **Required Skills** - Proficient in Python, version control (Git), automated testing, and CI/CD practices. - Hands‑on experience with leading ML frameworks: PyTorch, TensorFlow, or HuggingFace. - Familiarity with model serving and deployment tools, distributed systems, and data infrastructure. - Strong software engineering mindset: clean code, reusable components, performance profiling. - Ability to balance research creativity with operational reliability and scalability. - Excellent collaboration and communication skills across data science, engineering, and operations teams. **Preferred Experience** - Knowledge of large language models, multimodal systems, or time‑series forecasting. - Exposure to MLOps platforms and ML lifecycle tooling. - Background in ML research or solid understanding of ML theory. **Required Education & Certifications** - Bachelor’s degree (or equivalent) in Computer Science, Mathematics, Physics, or related technical discipline. - Minimum 1 year of professional software engineering/ML production experience; 7–15 years preferred. ---

New york, United states

Hybrid

Senior

15-11-2025

Company Name

Two Sigma

Job Title

Quantitative Researcher: Machine Learning

Job Description

Job Title: Quantitative Researcher: Machine Learning Role Summary: Develop and validate machine learning and statistical models to generate investment insights and trading strategies across global markets. Expectations: Deliver evidence‑based model solutions, collaborate with engineering, and engage in continuous learning through research literature and academic events. Key Responsibilities: - Apply rigorous scientific methodology to design sophisticated trading models. - Engineer and test machine learning pipelines on diverse datasets. - Translate model findings into actionable trading ideas in partnership with engineers. - Review and synthesize current research papers and academic seminars. - Present insights at internal and external conferences. Required Skills: - Proficiency in statistical analysis and machine learning algorithms. - Intermediate programming skills in C, C++, Java, or Python. - Experience tuning machine learning models for real‑world data. - Strong analytical and quantitative problem‑solving abilities. - Excellent communication for presenting technical findings. Required Education & Certifications: - Bachelor’s, Master’s, or Ph.D. in statistics, mathematics, physics, electrical engineering, computer science, or related quantitative field. - Published research or conference presentations in relevant domains preferred.

New york, United states

Hybrid

24-11-2025

Company Name

Two Sigma

Job Title

Software Engineering Full-Time Campus Hire - London

Job Description

Job Title: Software Engineer (Full-time Campus Hire) Role Summary: Software Engineer responsible for designing, building, and maintaining scalable, high‑performance systems that support Two Sigma’s data analysis and trading operations. Works across distributed storage, cloud environments, model testing/deployment, trading execution, and data ingestion pipelines. Partners with corporate teams to develop productivity tools and ensures reliability of mission‑critical infrastructure. Expectations: - Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Mathematics, or related quantitative field. - Strong programming ability in Java, C, C++, Python, Ruby, or Perl (JVM target). - Experience designing and operating large‑scale distributed systems. - Demonstrated analytical, organizational, and interpersonal skills. - Passion for writing clean, high‑quality code and solving complex technical problems. Key Responsibilities - Build core infrastructure used by multiple engineering teams (distributed storage, cloud services). - Develop and maintain high‑availability systems for primary trading platform. - Create and support environments for model testing and deployment. - Construct low‑latency, high‑performance execution pipelines for trading. - Scale data ingestion from 10,000+ daily sources. - Collaborate with corporate entities to design tools that increase organizational efficiency. Required Skills - Proficiency in Java, C, C++, Python, Ruby, or Perl (JVM). - Strong understanding of distributed systems, networking, and storage. - Experience with cloud platforms (public/private) and containerization. - Familiarity with performance tuning, low‑latency programming, and system reliability. - Ability to write clean, maintainable code and perform rigorous testing. - Excellent communication and teamwork capabilities. Required Education & Certifications - Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or related technical field. - No mandatory financial domain certification; generic professional certifications (e.g., AWS, GCP) are a plus but not required.

London, United kingdom

Hybrid

06-12-2025