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Data Science Faculty Jobs in Washington (NOW HIRING)

Cmu

Data Scientist

Arlington, VA · On-site

You'll get a chance to work with elite cybersecurity professionals and university faculty to build ... If you are a data science or statistics expert with an interest in cybersecurity, we want to hear ...

Carnegie Mellon University

Data Scientist

Arlington, VA · On-site

You'll get a chance to work with elite cybersecurity professionals and university faculty to build ... If you are a data science or statistics expert with an interest in cybersecurity, we want to hear ...

Cmu

Associate Data Scientist

Arlington, VA · On-site

$67K - $68K/yr

You'll get a chance to work with elite cybersecurity professionals and university faculty to build ... If you are a data science or statistics expert with an interest in cybersecurity, we want to hear ...

Cmu

Senior Data Scientist

Arlington, VA · On-site

You'll get a chance to work with elite cybersecurity professionals and university faculty to build ... If you are a data science or statistics expert with an interest in cybersecurity, we want to hear ...

Umd

Senior Faculty Specialist

College Park, MD · On-site

University of Maryland's College of Education's Center for Educational Data Science and Innovation ... EDSI is seeking a highly skilled Senior Faculty Specialist (Data Scientist) to lead data-driven ...

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All JobsData Science Faculty JobsData Science Faculty Jobs in Washington

Data Science Faculty information

See Washington salary details

$25.8K

$107K

$214.7K

How much do data science faculty jobs pay per year?

As of Aug 13, 2026, the average yearly pay for data science faculty in Washington is $106,953.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,241.00 and $155,681.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a data science faculty?

To thrive as a Data Science Faculty member, you need advanced knowledge in statistics, machine learning, and programming, typically supported by a graduate degree (Master's or Ph.D.) in data science or a related field. Familiarity with tools such as Python, R, SQL, and data visualization platforms, as well as experience using learning management systems, is essential. Excellent communication, mentorship, and curriculum development skills help engage students and foster an effective learning environment. These skills enable faculty to teach complex concepts clearly, guide student research, and stay current in a rapidly evolving discipline.

What are some common challenges data science faculty members face when balancing teaching and research responsibilities?

Data Science Faculty often juggle multiple responsibilities, including designing and delivering course content, mentoring students, and conducting their own research. One common challenge is allocating sufficient time for both high-quality instruction and advancing research projects, which may have overlapping deadlines. Faculty members also need to stay current with rapidly evolving data science tools and techniques to ensure their teaching remains relevant. Successful faculty often collaborate with colleagues, involve students in research, and utilize strong organizational skills to manage these demands effectively.

What is the difference between Data Science Faculty vs Data Analyst?

AspectData Science FacultyData Analyst
Required CredentialsTypically requires a master's or PhD in Data Science, Statistics, or related fieldsOften requires a bachelor's or master's degree in Data Analysis, Statistics, or related areas
Work EnvironmentAcademic institutions, universities, research centersCorporate offices, consulting firms, or in-house data teams
Employer & Industry UsageEducational and research institutionsBusiness, finance, healthcare, marketing, and other industries
Common Search & Comparison IntentUnderstanding academic roles, teaching, research opportunitiesData interpretation, reporting, business insights

Data Science Faculty primarily focus on teaching and research within academic settings, requiring advanced degrees and engaging in scholarly activities. Data Analysts work in industry, analyzing data to generate actionable insights, often with less emphasis on research and more on practical data interpretation. While both roles involve data skills, their environments, responsibilities, and credentials differ significantly.

What is a data science faculty?

Data Science Faculty are educators and researchers who teach and conduct research in the field of data science at colleges or universities. They design and deliver courses on topics such as statistics, machine learning, data analysis, and programming. In addition to teaching, they often mentor students, publish research, and may collaborate with industry partners on real-world data projects. Their goal is to advance knowledge in data science and prepare students for careers in this rapidly growing field.
Data Science Faculty jobs near you
Infographic showing various Data Science Faculty job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $106,953 per year, or $51.4 per hour.

Data Scientist

Cmu

Arlington, VA • On-site

Full-time

Re-posted 5 days ago

Job description


What We Do:

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity challenges. In this role, you will work with our customers to identify areas where advanced statistical techniques can help tackle problems, plan and develop prototype solutions, and build out final products. You'll get a chance to work with elite cybersecurity professionals and university faculty to build new technologies that will influence national cybersecurity strategy for decades to come. You will co-author research proposals, execute studies, and present findings to DoW sponsors and at academic conferences.
Our team works on a wide range of projects. Our current work includes research in generative AI and large language models, computer vision, multimodal AI, agentic AI, and assurance of AI systems. Additionally, we craft metrics and experimental designs for large-scale cybersecurity research programs, develop human-in-the-loop machine learning solutions, and build classifiers to identify security vulnerabilities. If you are a data science or statistics expert with an interest in cybersecurity, we want to hear from you!
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 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.

Knowledge, Skills and Abilities:

  • 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)

Desired Experience:

  • Experience in cybersecurity and privacy is a plus is a plus
  • Experience in U.S. Government work and/or with FFRDCs, UARCs an National Labs is a plus
  • Demonstrated ability to learn new concepts and grow into new areas of work

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

CMU logo

About CMU

Sourced by ZipRecruiter

Industry

Offices of mental health practitioners

Company size

201 - 500 Employees

Headquarters location

Harrisburg, PA, US

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