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Statistical Learning Jobs in Pennsylvania (NOW HIRING)

The Pennsylvania State University

The successful candidate will have a strong foundation in machine learning, artificial intelligence, statistical learning, scientific computing, data science, or related computational approaches.

KG Tiger

Statistical Programmer

Plymouth Meeting, PA

... learning, SPSS Excellent communication and interpersonal skills Qualifications Master's degree/Ph.D. in Statistics, Mathematics or related field with two to five years of experience OR a Bachelor ...

Citizens

Fraud Risk Analytics Manager

Philadelphia, PA · Hybrid

$106K - $130K/yr

Solid foundation in data science and statistical learning , including: * Classification and regression techniques * Feature engineering * Model evaluation and performance monitoring Preferred ...

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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 are popular job titles related to Statistical Learning jobs in Pennsylvania?

For Statistical Learning jobs in Pennsylvania, the most frequently searched job titles are:

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

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

What cities in Pennsylvania are hiring for Statistical Learning jobs?

Cities in Pennsylvania with the most Statistical Learning job openings:

Statistical Learning jobs near you

Senior Machine Learning Engineer - Mission Innovation Lab

Software Engineering Institute | Carnegie Mellon University

Pittsburgh, PA • On-site

$101K - $139K/yr

Full-time

Re-posted 28 days ago

Job description

Job Summary:
Carnegie Mellon University's Software Engineering Institute is seeking a Senior Machine Learning Engineer for their Mission Innovation Lab. The role involves leading applied-research projects to develop mission-scale AI capabilities for defense-focused missions, while collaborating with researchers and mentoring junior team members.
Responsibilities:
• Design, implement, and evaluate state‑of‑the‑art ML models (computer‑vision, NLP, planning, etc.) using frameworks such as TensorFlow, PyTorch, Torch, or Caffe.
• Build and maintain robust data pipelines, ETL processes, and backend services in Python, C/C++, and Java.
• Lead rapid‑prototyping efforts, translate research results into operational prototypes, and test for performance, robustness, and security.
• Define and refine DevSecOps practices for ML (model registries, containerized deployment, continuous integration/continuous delivery, security scanning).
• Mentor junior team members, collaborate with researchers, government customers, and other engineers, and contribute to technical strategy for the lab.
Qualifications:
Required:
• B.S. in Computer Science, Electrical Engineering, Statistics, or related field with ≥10 years of experience; OR M.S. with ≥8 years; OR Ph.D. with ≥5 years of relevant experience.
• Ability to obtain and maintain an active Department of War security clearance.
• You must be able and willing to work onsite 5 days per week at an SEI office in either Pittsburgh, PA or Arlington, VA.
• Strong experience in one or more programming language such as Python, C/C++, and Java; comfortable developing production-grade code and APIs.
• Solid understanding of ML theory, statistical learning, and common algorithms.
• Hands-on experience with TensorFlow, PyTorch, Torch, Caffe, or similar deep-learning libraries.
• Familiarity with CI/CD pipelines, container orchestration (Docker/Kubernetes), model versioning, and security-focused tooling.
Preferred:
• Proven track record of independent applied-research projects that resulted in demonstrable prototypes or operational capabilities.
• Publications or open-source contributions in AI and ML, especially in adversarial or robust ML.
• Experience working on defense or other high-impact government programs.
• Ability to quickly learn emerging AI and ML technologies and translate them into mission-relevant solutions.
Company:
We conduct cutting-edge research and development that accelerates the transition of technology to the Department of War (DoW), delivering measurable impact in support of the national security mission. Founded in 1984, the company is headquartered in Pittsburgh, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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