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Statistical Learning Jobs (NOW HIRING)

Morgan Stanley

Machine Learning Researcher

Broadway, VA · On-site

$154K - $213K/yr

Deep understanding of statistical learning methods * Strong communications and organizational skills * 4+ years of applicable research experience * Bachelor's degree required, Ph.D. desired #LI-SK1 ...

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Statistical Learning information

What are the key skills and qualifications needed to thrive as a Statistical Learning Specialist, and why are they important?

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.

What is statistical learning?

Statistical learning is a field within data analysis and machine learning that focuses on understanding and modeling the relationship between variables using statistical methods. It involves techniques such as regression, classification, and pattern recognition, often utilizing tools like R or Python. Professionals in this area analyze data to make predictions or inform decisions based on statistical models.

What jobs make $1,000,000 a year?

In the field of statistical learning, high-paying roles such as data science executives, chief data officers, or senior machine learning engineers can reach or exceed $1,000,000 annually, especially in large tech companies or finance firms. These positions typically require advanced skills in statistical modeling, programming, and experience managing large datasets, often combined with performance-based bonuses and stock options.

What careers can you get with statistics?

A career in statistical learning can lead to roles such as data analyst, data scientist, statistician, machine learning engineer, and quantitative researcher. These positions typically require skills in programming, data analysis, and statistical software, and are common in industries like finance, healthcare, technology, and government. Certifications in data analysis or machine learning can enhance job prospects.

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.

Is 40 too late for data science?

Statistical learning roles in data science do not have strict age limits, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be developed through online courses, certifications, and practical experience regardless of age.

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.

More about Statistical Learning jobs
What cities are hiring for Statistical Learning jobs? Cities with the most Statistical Learning job openings:
What states have the most Statistical Learning jobs? States with the most job openings for Statistical Learning jobs include:
What job categories do people searching Statistical Learning jobs look for? The top searched job categories for Statistical Learning jobs are:
Statistical Learning jobs near you
Infographic showing various Statistical Learning job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.
Senior Machine Learning Engineer - Mission Innovation Lab

Senior Machine Learning Engineer - Mission Innovation Lab

Software Engineering Institute

Pittsburgh, PA • On-site

$101K - $139K/yr

Full-time

Re-posted 14 days ago

Job description

At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of AI technologies and systems. We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security.
As our government customers adopt AI and machine learning to provide leap-ahead mission capabilities, we
  • build real-world, mission-scale AI capabilities through solving practical engineering problems

  • discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities

  • prepare our customers to be ready for the unique challenges of adopting, deploying, using, and maintaining AI capabilities

  • identify and investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape

Are you creative, curious, energetic, collaborative, technology-focused, and hard-working? Are you interested in making a difference by bringing innovation to government organizations and beyond? Apply to join our team.
Overview
As a Machine Learning Engineer who can take research ideas from concept to prototype, you will lead independent applied-research projects for defense-focused missions.
The ideal candidate is comfortable across the full stack (data pipelines, model development, API services, and secure deployment) and eager to explore novel AI and ML theory while delivering mission-scale capabilities.
The Mission Innovation Lab within the SEI's AI Division works with the defense and national security community to translate the "recently possible" in AI into reliable mission and warfighting capabilities.
Key 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.

Required Qualifications
  • 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.

Desired Experience
  • 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.

Knowledge, Skills, & Abilities
  • Deep technical knowledge of modern ML methods and ability to extend them to novel domains.

  • Excellent written and verbal communication skills; capable of presenting complex ideas to technical and non-technical audiences.

  • Strong collaborative mindset; experience working in interdisciplinary teams and mentoring peers.

  • High degree of scientific curiosity and a proactive, self-directed work style.

Location
Arlington, VA, Pittsburgh, PA
Job Function
Software/Applications Development/Engineering
Position Type
Staff - Regular
Full time/Part time
Full time
Pay Basis
SalaryMore Information:
  • Please visit "Why Carnegie Mellon" to learn more about becoming part of an institution inspiring innovations that change the world.
  • Click here to view a listing of employee benefits
  • Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.
  • Statement of Assurance

Apply