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Data Science Phd Jobs in Washington, DC (NOW HIRING)

Smart Data

Data Scientist III

Chantilly, VA · On-site

This role focuses on applying data science, machine learning, and data engineering techniques to ... PhD in a relevant field with 3+ years of experience; or an equivalent combination of education and ...

Posted today

Capital One

Manager, Data Science

Mclean, VA · On-site

... or a PhD or foreign equivalent degree in the aforementioned fields and 1 year of experience as ... McLean, VA * $170,872.00 - $267,900.00 for Manager, Data Science Candidates hired to work in other ...

Capital One

Manager, Data Science

Mclean, VA · On-site +1

... or a PhD or foreign equivalent degree in the aforementioned fields and 1 year of experience as ... McLean, VA * $170,872.00 - $267,900.00 for Manager, Data Science Candidates hired to work in other ...

VTG

Data Scientist

Chantilly, VA · On-site

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field (PhD preferred for some roles) * 5+ years of experience in data science or a related field

VT Group (VTG)

Data Scientist

Chantilly, VA · On-site

Required : • Active TS/SCI with Polygraph required. • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field (PhD preferred for some roles) • ...

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Data Science Phd information

What is a data science PhD?

A Data Science PhD is a doctoral-level degree focused on advanced research in data science, which combines elements of statistics, computer science, and domain expertise. Students in a Data Science PhD program typically work on developing new methods for analyzing large datasets, creating machine learning algorithms, and addressing complex problems in areas such as artificial intelligence, data mining, and predictive analytics. Graduates are prepared for careers in academia, research, and industry, where they can lead data-driven projects and contribute to advancements in the field.

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

To thrive as a Data Science PhD, you need advanced expertise in statistics, machine learning, data analysis, and a doctoral degree in a quantitative field. Proficiency in programming languages like Python or R, experience with big data frameworks (e.g., Spark, Hadoop), and familiarity with data visualization tools are typically required. Critical thinking, problem-solving, and strong communication skills help you translate complex data insights for diverse stakeholders. These skills are vital for driving innovative research, making data-driven decisions, and contributing impactful solutions in data-centric environments.

What are some common challenges faced by data science PhDs when transitioning from academia to industry roles?

Data Science PhDs often encounter challenges such as adapting to the faster pace and collaborative nature of industry projects compared to academic research. In industry, there is a greater emphasis on delivering practical solutions within tight deadlines and working closely with cross-functional teams like engineering and product management. Additionally, data science work in industry may require balancing technical rigor with business impact, often prioritizing actionable insights over exhaustive analysis. Building strong communication and stakeholder management skills can help ease this transition.

What can I do with a data science PhD?

A data science PhD prepares individuals for advanced roles in research, analytics, and machine learning across industries such as technology, finance, healthcare, and academia. Graduates can work as data scientists, machine learning engineers, research scientists, or data analysts, often utilizing programming languages like Python or R and tools such as TensorFlow or SQL. The degree also enables roles involving complex data modeling, statistical analysis, and developing innovative data-driven solutions.

What are popular job titles related to Data Science Phd jobs in Washington, DC?

For Data Science Phd jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Data Science Phd jobs in Washington, DC look for?

The top searched job categories for Data Science Phd jobs in Washington, DC are:

Data Science Phd jobs near you
Infographic showing various Data Science Phd job openings in Washington, DC as of August 2026, with employment types broken down into 27% Internship, and 73% Full Time. Highlights an 100% In-person job distribution.

Data Scientist III

Smart Data

Chantilly, VA • On-site

Full-time

Posted 16 hours ago

Posted today

Job description

Data Scientist III


Chantilly, VA (on-site at client facility)


Full-Time, Long-Term Contract (1-Year Assignment, Temp-to-Perm Possible)


Clearance Required: Active TS/SCI with Polygraph (Required — must be a U.S. Citizen)


Job Summary


We are seeking a Data Scientist III to support a mission-critical program in the Chantilly, VA area. This role focuses on applying data science, machine learning, and data engineering techniques to advanced science and technology (S&T) mission challenges. The ideal candidate is technically curious, comfortable working across diverse and multi-source data, and skilled at turning complex data into actionable insight.


Responsibilities


- Collect, organize, and analyze technical information from multiple sources to drive mission objectives and quick-turn tasks in fast-paced environments

- Aid in the design and implementation of machine learning and data engineering techniques applied to advanced S&T missions

- Apply technical proficiency in data collection and analysis tools to S&T mission areas, improving existing techniques and devising new ones to solve mission-critical data science challenges

- Collaborate in a multi-disciplinary environment while working independently and leading tasks on time and on budget

- Independently propose, develop, and execute creative solutions to unique data science problems, including suggestions for new data sources and data exploitation techniques

- Deliver thorough, polished work products requiring only minor revision

- Proactively manage expectations and meet deadlines in a fast-moving, agile environment

- Maintain excellent communication with both co-located and geographically dispersed team members


Required Qualifications


- Experience using tools for collecting, assembling, interpreting, translating, and analyzing multi-source data (S&T information, network, open source, databases) and synthesizing it into actionable intelligence

- Experience applying machine learning, statistics, and/or data mining techniques to gain insights from data

- Experience automating data pipelining processes, data transformation, databases, and/or repositories

- Experience assessing and technically reporting on technologies and scientific topics (e.g., Technology Readiness Levels (TRL) and Critical Technology Elements (CTE))

- Experience working with diverse media and advanced S&T data

- BS with 8+ years of relevant experience; MS with 5+ years of relevant experience; PhD in a relevant field with 3+ years of experience; or an equivalent combination of education and experience in a relevant field

- Genuine excitement for learning new technical subject areas and curiosity about S&T missions

- Experience supporting national security, defense, and/or intelligence community missions

- Must be a U.S. Citizen with an active TS/SCI clearance with polygraph (non-negotiable)


Additional Details


- Assignment Length: 1 year (temp-to-perm possible)

- Schedule: Standard hours (40/week)

- Work Location: On-site required

- Interview Process: Video interview with hiring manager and technical team

- Relocation Candidates: Will consider hiring via video interview for non-local candidates willing to relocate

- Target Start Date: 09/01/2026


Smart Data Systems is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, age, or any other protected characteristic under applicable federal, state, or local law.