Point72 Logo

Point72

Data Scientist

Reposted 13 Hours Ago
In-Office
New York, NY, USA
Junior
In-Office
New York, NY, USA
Junior
Data Scientists at Cubist will analyze data, engineer features for models, and work with quantitative researchers on trading strategies.
The summary above was generated by AI

About Cubist

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

Role

Data Scientists bridge the gap between raw data and predictive modelling. We believe everything starts with data. You will work closely with our quantitative research team, applying advanced techniques to engineer, validate, and refine features that feed directly into our systematic models. This is a role within an established investment team, offering opportunities for progression into more senior research responsibilities across the full trading pipeline.

Responsibilities

  • Conduct thorough data analysis under the mentorship of a senior quantitative researcher.
  • Generate novel ideas for enhanced proprietary data products.
  • Track and evaluate new offerings from internal and external data vendors in partnership with Compliance.
  • Transform firm approved raw datasets into robust features for our systematic models.
  • Build analytical tools to supplement our shared research framework.

Requirements

  • BS, MS or PhD in finance, economics, mathematics, statistics, data science, computer science, or other quantitative discipline.
  • Programming in Python (or a comparable language) and working knowledge of SQL.
  • Strong analytical and quantitative skills.
  • Willingness to take ownership of their work.
  • Ability to work both independently and collaboratively within a team.
  • Strong desire to deliver high quality results in a timely fashion.
  • High attention to detail.
  • Prior experience as a data analyst, data sourcing specialist, or data scientist for a financial firm is a plus
  • Commitment to the highest ethical standards.

Point72 New York, New York, USA Office

55 Hudson Yards , New York, United States, 10001

Similar Jobs

Yesterday
Hybrid
New York, NY, USA
100K-143K Annually
Senior level
100K-143K Annually
Senior level
Artificial Intelligence • Cloud • Fintech • Information Technology • Insurance • Financial Services • Big Data Analytics
Contribute to enterprise AI initiatives by developing, validating, and operationalizing ML and generative/agentic AI solutions. Work across the model lifecycle (data exploration, feature engineering, training, deployment, monitoring) using AWS, Snowflake, and Databricks; implement LLM/RAG approaches, APIs, lightweight UI prototypes, and adhere to responsible AI, governance, and MLOps practices.
Top Skills: Aws BedrockAws SagemakerDatabricksEmbeddingsGitGitLlmsMlopsPrompt EngineeringPythonRagSnowflakeSQLStreamlitVector Stores
Yesterday
Hybrid
New York, NY, USA
72K-212K Annually
Senior level
72K-212K Annually
Senior level
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Use advanced analytics, statistical methods, and machine learning to transform large datasets into actionable insights. Build data solutions and pipelines, perform exploratory analysis, create visualizations, validate models (including generative AI and NLP), collaborate with clients, mentor juniors, and maintain data quality to inform strategic decisions.
Top Skills: Data EngineeringData PipelinesData Science LibrariesDeep LearningGenerative AiMachine LearningModel ValidationNatural Language ProcessingPythonStatistical Analysis
Yesterday
Hybrid
New York, NY, USA
99K-297K Annually
Mid level
99K-297K Annually
Mid level
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Lead data science initiatives within Data and Analytics Engineering to build predictive models, maintain data pipelines and lakes, apply ML/DL and generative AI, ensure data quality, coach teams, manage project timelines, and collaborate with stakeholders to drive data-driven business growth.
Top Skills: Data EngineeringData LakesData PipelinesData Science LibrariesDeep LearningGenerative AiMachine LearningModel Validation MethodsPython

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account