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Algorithm Research Jobs in Edison, NJ (NOW HIRING)

New York University

Research Intern

New York, NY · On-site

$48K - $62K/mo

Description RESEARCH INTERNSHIP Department of Computer Science and Engineering New York University ... They should have a strong background in AI/ML, biometric algorithm design and evaluation, and ...

New York University

RESEARCH SCHOLAR

New York, NY · On-site

... algorithms for biomedical engineering applications * conducting human subject research including ... physiological health data collection * data analysis The successful candidate will have a ...

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Algorithm Research information

What is algorithm research?

Algorithm research involves studying, designing, analyzing, and optimizing algorithms to solve complex problems efficiently. Researchers in this field explore new computational methods, improve existing algorithms, and evaluate their performance in various contexts. This work is fundamental in areas like computer science, artificial intelligence, data science, and cryptography, driving technological advances and innovation.

What are the key skills and qualifications needed to thrive as an algorithm researcher?

To excel as an Algorithm Researcher, you need a strong background in mathematics, computer science, and algorithm design, often supported by an advanced degree such as a master's or PhD. Proficiency with programming languages (like Python, C++, or Java), machine learning frameworks, and version control systems is essential. Analytical thinking, creativity, and effective communication are crucial soft skills that set top performers apart in this field. These skills are vital for developing innovative, efficient solutions and collaborating within interdisciplinary teams to solve complex computational problems.

What are the typical challenges faced by professionals in algorithm research roles and how can they best address them?

Algorithm Research professionals often encounter challenges such as bridging the gap between theoretical solutions and practical implementation, staying updated with rapid advancements in the field, and collaborating with cross-functional teams to integrate research outcomes into real-world products. To address these challenges, it is helpful to maintain strong communication with engineering teams, participate in continual learning through academic papers and conferences, and adopt an iterative approach to testing and refining algorithms. Building a habit of documenting experiments and results also streamlines collaboration and future development.

What is the difference between Algorithm Research vs Data Scientist?

AspectAlgorithm ResearchData Scientist
Required CredentialsAdvanced degrees in CS, Mathematics, or related fieldsDegree in CS, Statistics, or related fields; certifications like SAS or Python
Work EnvironmentResearch labs, R&D departments, academiaBusiness environments, analytics teams, tech companies
Industry UsageDeveloping new algorithms, theoretical researchAnalyzing data, building predictive models, insights generation
Common Search/ComparisonYesNo

Algorithm Research focuses on developing and testing new algorithms, often in research or academic settings, requiring advanced technical credentials. Data Scientists analyze data to generate insights and build models, working primarily in business environments. While both roles involve data and programming, their core objectives and work settings differ significantly.

What are popular job titles related to Algorithm Research jobs in Edison, NJ?

For Algorithm Research jobs in Edison, NJ, the most frequently searched job titles are:

What job categories do people searching Algorithm Research jobs in Edison, NJ look for?

The top searched job categories for Algorithm Research jobs in Edison, NJ are:

What cities near Edison, NJ are hiring for Algorithm Research jobs?

Cities near Edison, NJ with the most Algorithm Research job openings:

Algorithm Research jobs near you
Infographic showing various Algorithm Research job openings in Edison, NJ as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Quantitative Researcher - Machine Learning

New York, NY • On-site

Point72
Finance and Insurance • 501 - 1,000 employees
Learn more about Point72external

Full-time

Re-posted 6 days ago

Job description

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/Responsibilities:

We are seeking a quantitative researcher for the Cubist Machine Learning Research group with experience in machine learning, especially recent deep learning and natural language processing technology.

Researchers will use a rigorous scientific method to develop sophisticated trading models and shape our insights into how the markets will behave.  Successful researchers manage all aspects of the research process including data ingestion and processing, data analysis, methodology selection, implementation and testing, prototyping, and performance evaluation.

Researchers will be introduced to industry standard datasets, including understanding which data may be relevant to a certain model or financial problem; how to collect, parse, and clean the data; how to incorporate the data into innovative functional models; how to construct and develop features from raw data; and how to estimate effectiveness of such features.

Researchers will also be provided with the opportunity to implement the full breadth of their knowledge and training to actively participate in all stages of research & development of financial models through use of machine learning. Based on experience from working with existing industry-standard models and algorithms, researchers will learn how to construct their own models in order to solve complex financial problems and enhance data prediction capabilities within the financial services industry. 

Requirements:

  • PhD or PhD candidate in machine learning, computer science, statistics, or a related field
  • Experience with sequential modeling and time series forecasting using deep learning
  • Experience with deep neural networks and representation learning
  • Prior experience working in a data driven research environment
  • Experience with translating mathematical models and algorithms into code
  • Proficient in programming languages such as Python and R
  • Experience with machine learning software libraries such as TensorFlow or PyTorch
  • Experience with natural language processing technology a strong plus
  • Excellent analytical skills, with strong attention to detail
  • Interest in applying machine learning to finance
  • Collaborative mindset with strong independent research ability
  • Strong written and verbal communication skills

We're looking for exceptional colleagues with unparalleled passion. If you'd like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that you've worked outside of school, or as part of your curriculum. If you're proud of the work you did we want to hear about it. In addition to exceptional statisticians and engineers, we work with talented musicians, writers, mathematicians, and founders of non-profits; we'd love to learn more about what excites you.

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