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Computer Science Statistics Jobs in Pennsylvania

Cmu

Data Scientist

Pittsburgh, PA · On-site

Requirements: * BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with eight (8) years of experience or equivalent combination of training ...

Cmu

Senior Data Scientist

Pittsburgh, PA · On-site

Requirements: * BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with ten (10) years of experience or equivalent combination of training ...

Cmu

Associate Data Scientist

Pittsburgh, PA · On-site

$57K - $57K/yr

Requirements: * BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with three (3) years of experience or equivalent combination of training ...

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Computer Science Statistics information

Do computer science statisticians make a lot of money?

Computer science statisticians typically earn competitive salaries, especially with advanced skills in data analysis, programming, and statistical software. Salaries vary based on experience, education, and location, but the field generally offers strong earning potential compared to many other roles in technology and data science.

What is a computer science statistics?

A Computer Science Statistics job involves applying statistical methods and data analysis techniques to solve problems in computing, artificial intelligence, and software development. Professionals in this field work with large datasets, develop predictive models, and optimize algorithms for machine learning, cybersecurity, and data science applications. They may work in industries such as finance, healthcare, or technology, using statistical reasoning to enhance decision-making and efficiency. Strong programming skills, knowledge of probability theory, and experience with data visualization are typically required.

What jobs do most computer science statistics majors get?

Computer science statistics majors often find employment as data analysts, data scientists, machine learning engineers, and software developers. These roles typically require skills in programming languages like Python or R, statistical analysis, and data visualization tools. Many positions are available in technology, finance, healthcare, and consulting industries.

Is statistics useful in computer science?

Statistics is highly useful in computer science, especially for data analysis, machine learning, and algorithm development. It provides essential tools for interpreting data, making predictions, and optimizing systems, which are core skills in many computer science roles.

What do computer science statistics professionals do?

Professionals in Computer Science Statistics roles frequently work on projects involving data analysis, predictive modeling, and the development of algorithms to extract insights from large datasets. Their typical responsibilities include cleaning and preparing data, designing and running statistical tests, coding custom analytics solutions, and visualizing results for reports or presentations. Collaboration with teams such as data engineers, software developers, and business analysts is common to ensure that statistical models effectively address real-world business problems. This role offers opportunities to work across diverse industries, allowing for continual learning and skill development.

What skills and qualifications are needed for computer science statistics?

To excel in a Computer Science Statistics role, a strong background in both statistical analysis and computer science principles, usually backed by a degree in a related field, is essential. Expertise in programming languages like Python or R, experience with statistical software, and familiarity with databases or machine learning libraries are highly valued. Analytical thinking, attention to detail, and effective communication are key soft skills that differentiate top performers in this position. Mastery of these skills enables professionals to accurately interpret data, develop robust analytical solutions, and clearly convey complex findings to both technical and non-technical stakeholders.

What are the most commonly searched types of Computer Science Statistics jobs in Pennsylvania?

The most popular types of Computer Science Statistics jobs in Pennsylvania are:

What are popular job titles related to Computer Science Statistics jobs in Pennsylvania?

For Computer Science Statistics jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Computer Science Statistics jobs in Pennsylvania look for?

The top searched job categories for Computer Science Statistics jobs in Pennsylvania are:

Computer Science Statistics jobs near you
Infographic showing various Computer Science Statistics job openings in Pennsylvania as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 75% Full Time, 19% Part Time, 2% Contract, and 2% Nights. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution.

Data Scientist

Software Engineering Institute | Carnegie Mellon University

Pittsburgh, PA • On-site

Full-time

Re-posted 7 days ago

Job description

Job Summary:
Carnegie Mellon University's Software Engineering Institute is seeking a Data Scientist to leverage advanced statistics, data analytics, machine learning, and artificial intelligence to address cybersecurity challenges. The role involves collaborating with clients to develop prototype solutions, conducting research, and presenting findings at conferences.
Responsibilities:
• Identify areas where advanced statistical techniques can help tackle problems.
• Plan and develop prototype solutions.
• Build out final products.
• Co-author research proposals.
• Execute studies and present findings to DoW sponsors and at academic conferences.
Qualifications:
Required:
• BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with eight (8) years of experience or equivalent combination of training or experience; or MS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with five (5) years of experience; or PhD in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with two (2) years of experience.
• Willingness to complete modest travel to various locations to support the SEI’s overall mission.
• You will be subject to a background check and must be able obtain and maintain a U.S. Department of War security clearance.
• Experience in predictive modeling, data science, and/or AI & machine learning
• Deep understanding of statistical modeling techniques and advanced data analytics
• Proficient with at least one mathematical/statistical programming package (e.g., R, python numpy/scipy/pandas/polars, MATLAB, etc.)
• Innovative and inquisitive with ability to imagine novel analytical solutions to problems
• Thrives in a multi-disciplinary environment
• Strong communication skills
• Expertise in one or more of the following: Recommendation systems, Time-series forecasting (Prophet, NeuralProphet, Chronos, Lag-Llama, etc.), NLP / LLMs (fine-tuning, RAG, evaluation, prompt engineering), Causal inference / uplift modeling / synthetic controls, Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch, JAX, TensorFlow), LLMs / agentic workflows (LangChain/LlamaIndex/Haystack), Experience deploying models (FastAPI, Triton, KServe, SageMaker, Vertex AI, or similar), Experience working with big data (Spark, Trino, Snowflake, BigQuery, Databricks)
Preferred:
• Experience in cybersecurity and privacy is a plus
• Experience in U.S. Government work and/or with FFRDCs, UARCs and National Labs is a plus
• Demonstrated ability to learn new concepts and grow into new areas of work
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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