Quantitative researcher for the Cubist Machine Learning Research group, developing trading models using deep learning and NLP.
Responsibilities
Develop sophisticated trading models using machine learning
Manage all aspects of the research process including data ingestion, analysis, methodology selection, implementation, testing, prototyping, and performance evaluation
Requirements
PhD or PhD candidate in machine learning, computer science, statistics, or a related field
Nice to have: experience in a data driven research environment
Nice to have: experience with financial models
Nice to have: interest in applying machine learning to finance
We are looking for a quantitative software developer to join our team and contribute to multiple initiatives that aim to expand our business. The candidate should be passionate about financial market, data and technology. In this team, the candidate will gain full-stack exposure and build expertise in multiple aspects of quantitative trading.
Responsibilities
Improve data ETL pipeline and build tools to analyze new data efficiently.
Build technologies to bolster research & trading efficiency.
Expand to new markets and asset classes.
Manage day-to-day operations in a fast-paced environment.
The Data Scientist will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure and the live production trading of billions of dollars of capital across global capital markets.
Responsibilities
Onboarding novel datasets from a huge variety of sources into our platform
Develop, test and deploy data pipelines, applications and services
Re-shaping, aggregating, enhancing and creating features from datasets
Engaging with vendors and internal stakeholders to understand characteristics of datasets
Defining and automating qualitative data alerts and reports
Maintain and support the CLO and Loans trading system and other internal applications.
Compensation
The base pay range for this position in New York is $100,000 - $150,000 annually. Pay may vary depending on job-related knowledge, skills, and experience. Equity and year-end bonus may be provided as part of the compensation package, in addition to a full range of medical, financial, and other benefits, dependent on the position offered.
Responsibilities
Maintain and support production, demonstration and test systems
Ensure high availability of systems
Resolve system problems in a timely and professional manner
Proactively learn and understand business needs
Develop or implement solutions to meet business needs
Rackner is seeking a Data Integration Engineer to build and maintain secure, reliable data pipelines supporting mission-critical federal healthcare technology operations.
Responsibilities
Design, develop, and maintain secure, API-based data pipelines connecting approved operational systems with a designated enterprise analytics environment.
Operate and troubleshoot assigned data integrations to support reliable, consistent delivery of information for analytics and assurance activities.
Automate the collection and processing of operational metric inputs to reduce manual effort and improve reporting reliability.
Develop repeatable data and evidence extraction workflows that support authorized analysis and independent assurance activities.
Apply version control, testing, and established CI/CD processes to validate and deliver data integration changes.
The New York Times is seeking inventive and motivated interns to join the Machine Learning Science group to develop and deploy machine learning solutions.
Compensation
The hourly rate of base pay for this role is: $40—$40 USD
Responsibilities
Develop and deploy machine learning solutions to newsroom and business problems
Work with Python and tools such as scikit-learn and Google Cloud Platform
Communicate the results of your analyses to other members of the organization in a clear and concise fashion
Demonstrate support and understanding of our value of journalistic independence
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