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Statistical Programming Intern Jobs in Brooklyn, NY

This includes designing, programming,and fielding a survey,analyzing the results, and building a ... Analyze survey results using Excel or statistical tools (e.g., SPSS, R, or similar) * Synthesize ...

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Statistical Programming Intern information

What does a statistical programming intern do?

A Statistical Programming Intern assists in analyzing data and creating statistical reports, often using software languages like SAS, R, or Python. They help design and implement data analysis plans, support senior statisticians or data scientists, and ensure data quality and integrity. Their work is crucial in fields like clinical research, finance, and marketing, where data-driven decision-making is essential. Interns gain hands-on experience with real-world datasets and learn best practices in data management and statistical analysis.

What types of projects or tasks can a statistical programming intern expect to work on during their internship?

As a Statistical Programming Intern, you will typically assist with data cleaning, preparation, and analysis for ongoing research or clinical studies. You might be responsible for writing and testing code in SAS, R, or Python to generate tables, listings, and figures, as well as supporting the development of statistical analysis plans. Interns often collaborate closely with biostatisticians, data managers, and clinical teams to ensure high-quality data outputs. This role offers valuable exposure to real-world datasets and best practices in statistical programming, providing a solid foundation for future roles in data science or biostatistics.

What are the key skills and qualifications needed to thrive as a statistical programming intern, and why are they important?

To thrive as a Statistical Programming Intern, you need a solid grounding in statistics, programming (often with R or SAS), and data analysis, typically supported by coursework or a degree in statistics, mathematics, or a related field. Familiarity with statistical software, version control systems like Git, and database tools is highly beneficial, alongside any relevant certifications in programming languages or analytics platforms. Attention to detail, analytical thinking, and effective communication are vital soft skills for interpreting data and collaborating with team members. These skills are important because they enable interns to accurately analyze data, contribute to research projects, and support informed decision-making in data-driven environments.

What is the difference between Statistical Programming Intern vs Data Analyst Intern?

AspectStatistical Programming InternData Analyst Intern
Required SkillsProgramming (R, SAS, Python), statistical methodsData analysis, Excel, SQL, visualization
Work EnvironmentPharmaceutical, biotech, or research labsBusiness, marketing, or finance sectors
Typical TasksData cleaning, statistical modeling, programmingData interpretation, reporting, dashboards

Both roles often require programming and data skills, but Statistical Programming Interns focus more on statistical modeling and programming tasks within research environments, while Data Analyst Interns handle broader data analysis and reporting in business settings. They share similar entry-level requirements but differ in industry focus and daily responsibilities.

What are the most commonly searched types of Statistical Programming jobs in Brooklyn, NY?

The most popular types of Statistical Programming jobs in Brooklyn, NY are:

What are popular job titles related to Statistical Programming Intern jobs in Brooklyn, NY?

For Statistical Programming Intern jobs in Brooklyn, NY, the most frequently searched job titles are:

What cities near Brooklyn, NY are hiring for Statistical Programming Intern jobs?

Cities near Brooklyn, NY with the most Statistical Programming Intern job openings:

Infographic showing various Statistical Programming Intern job openings in Brooklyn, NY as of August 2026, with employment types broken down into 1% Internship, 83% Full Time, 12% Part Time, 3% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution.

Campus AI Research Engineer - Deep Learning (Intern)

Jump Trading

Manhattan, NY • On-site

$300K/yr

Other

Re-posted 28 days ago


Job description

Campus Ai Research Engineer - Deep Learning (Intern)

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

We are seeking research scientists with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research and monetization process. We believe that successful research efforts require a fluid mix of skills including AI/ML expertise, engineering pragmatism, statistics, and market intuition.

What You'll Do:

  • Apply state-of-the-art techniques to complex and challenging domains.
  • Work closely with researchers and quants to build flexible and reusable frameworks for financial ML.
  • Optimize training pipelines to make the best use of our HPC resources.
  • Integrate ML models into production systems where latency matters.
  • Work across a mix of programming languages: C / C++ / Python / CUDA and other low-level GPU languages.
  • Build large-scale ML systems that are observable, performant, and flexible. Help improve productivity by reducing the iteration cycle time on research.
  • Other duties as assigned or needed.

Skills You'll Need:

  • Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent and/or contributions to open-source AI research
  • Strong general ML background with exposure to modern deep learning techniques and/or language modeling architectures (e.g. transformers, SSMs)
  • Solid development skills in Python and/or C++
  • Familiarity with ML libraries/frameworks such as PyTorch, JAX, and/or TensorFlow
  • Intellectual curiosity, versatility, and originality combined with a pragmatic outlook
  • Ability to thrive in a collaborative, team-oriented environment
  • Ability to reason through quantitative problems and communicate effectively with trading researchers
  • Reliable and predictable availability

Bonus Points:

  • Experience with HPC and distributed large model training
  • Experience with GPU performance optimization (CUDA or ROCm)
  • Experience with end-to-end model development
  • Strong opinions on best practices in ML research, tooling, and/or infrastructure

INTERNATIONAL STUDENTS are encouraged to apply. We accept students eligible for CPT/OPT and we sponsor work visas for full-time positions.

The estimated base salary for this role (annualized) is $300,000 per year.