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Statistical Learning Jobs in New York (NOW HIRING)

Systematic Equity Trader

Manhattan, NY ยท On-site

$150K - $225K/yr

Utilize sound financial insight and statistical learning techniques to explore, analyze, and harness a wide range of datasets building predictive models. * Design and implement short-term trading ...

Prediction Researcher

New York, NY ยท On-site

$200K - $600K/yr

Some problems are best solved with structured statistical or machine-learning methods. Others may benefit from language models, retrieval, tools, explicit decomposition, simulated agents, or a ...

To accomplish our aims, we're leveraging state of the art statistical learning and convex optimization methods (AI) to build the financial trust layer for the electric age. We envision energy systems ...

Showing results 41-60

Statistical Learning information

What are the key skills and qualifications needed to thrive as a statistical learning specialist?

To thrive as a Statistical Learning Specialist, you need a strong background in statistics, probability, and machine learning, typically supported by an advanced degree in statistics, mathematics, computer science, or a related field. Expertise with programming languages such as Python or R, experience with statistical software (e.g., SAS, MATLAB), and familiarity with data analysis libraries are essential. Critical thinking, problem-solving, and effective communication skills help translate complex data insights into actionable business strategies. These competencies are crucial for extracting meaningful patterns from data and driving data-informed decision-making.

How do professionals in statistical learning typically collaborate with data scientists and domain experts on projects?

Professionals in statistical learning often work closely with data scientists and domain experts to ensure that the models they develop are both statistically sound and practically relevant. Collaboration usually involves joint problem definition, sharing data insights, and iterative feedback on model performance. Statistical learning experts contribute their knowledge of algorithms and statistical methods, while data scientists handle data pre-processing and engineering, and domain experts provide context to interpret results. This multidisciplinary teamwork helps ensure that solutions are robust and actionable for stakeholders.

What is the difference between Statistical Learning vs Data Analyst?

AspectStatistical LearningData Analyst
Required CredentialsDegree in Statistics, Data Science, or related fieldsDegree in Statistics, Data Science, Business, or related fields
Work EnvironmentResearch, academia, tech companies, data science teamsBusiness, marketing, finance, healthcare organizations
Employer & Industry UsageTech firms, research institutions, startupsCorporations, consulting firms, government agencies
Common Search & ComparisonStatistical Learning vs Data Analyst

Statistical Learning focuses on developing models and algorithms to understand data patterns, often requiring advanced statistical and programming skills. Data Analysts interpret data to generate reports and insights, typically emphasizing data visualization and business understanding. While both roles analyze data, Statistical Learning is more research-oriented and technical, whereas Data Analysts focus on practical data interpretation for decision-making.

What will I become if I study statistical learning?

Studying statistical learning can lead to roles such as data scientist, data analyst, machine learning engineer, or statistician. These positions involve analyzing data, building predictive models, and applying statistical methods using tools like R or Python in various industries.

What job categories do people searching Statistical Learning jobs in New York look for?

The top searched job categories for Statistical Learning jobs in New York are:

What cities in New York are hiring for Statistical Learning jobs?

Cities in New York with the most Statistical Learning job openings:

Infographic showing various Statistical Learning job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Machine Learning Specialist

New York, NY โ€ข On-site

Applied Physics
Pharmaceutical and Medicine Manufacturingย โ€ขย 1 - 10 employees

Full-time

Re-posted 27 days ago


Job description

Applied Physics is seeking a highly motivated and skilled professional to join our Machine Learning team at the Advanced Propulsion Laboratory at Applied Physics. In this role, you will have the opportunity to work on cutting-edge research in new and emerging fields.

Responsibilities:

  • Conduct research on state-of-the-art Machine Learning algorithms relevant to the problem being addressed.
  • Implement, train, and validate proposed algorithms for specific problem domains.
  • Contribute to the integration of algorithms within larger programmatic systems that require these capabilities.
  • Collaborate with others in a multidisciplinary team environment to accomplish research goals.
  • Pursue both independent and collaborative research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.
  • Publish research results in peer-reviewed scientific journals and present results at conferences, seminars, and meetings.
  • Travel as required to coordinate research with collaborators and visit field sites.

Requirements

  • PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, or another technical discipline providing an underlying skillset in data analysis and Machine Learning techniques.
  • Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference (e.g., probabilistic graphical models, Gaussian processes, or nonparametric Bayesian methods).
  • Experience in the broad application of one or more higher-level programming languages such as Python, Java, Scala, or C/C++.
  • Experience with one or more deep learning libraries such as PyTorch, TensorFlow, Keras, or Caffe.
  • Proven ability to undertake original research and communicate findings in peer-reviewed publications.
  • Experience working with a multidisciplinary team of scientists, engineers, and project managers to develop and apply these capabilities to inform engineering decisions.
  • Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.

Benefits

We offer a competitive salary and benefits package, flexible work hours, and opportunities for growth and career development. Join our dynamic and passionate team and help us make a positive impact on the world.

If you are a talented, motivated, and empathetic individual who shares our passion for making a difference, we encourage you to apply for this exciting opportunity to work with our team at Applied Physics. Applied Physics is an equal opportunity employer.