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Data Scientist Project Manager Jobs in Reston, VA

JS Consulting

Data Scientist

Washington, DC · On-site

Job Title- Data Scientist Project Location - Onsite in Washington, District of Columbia Duration ... management. * Demonstrated experience programming with R/Python, Linux, and Spark in AWS cloud ...

Venture Global LNG

Senior Data Scientist

Arlington, VA · On-site

... project plans for implementing data science projects including solution architectures, resourcing ... managing, developing, and maintaining machine learning solutions. • Fundamental skills in data ...

VTG

Data Scientist

Chantilly, VA · On-site

Familiarity with the Agile (i.e., Scrum, Jira, Confluence) or equivalent project management process preferred, the Level 2 Data Scientist (Intermediate) is responsible for designing data science ...

VTG

Data Scientist

Chantilly, VA · On-site

Familiarity with the Agile (i.e., Scrum, Jira, Confluence) or equivalent project management process preferred, the Level 2 Data Scientist (Intermediate) is responsible for designing data science ...

BlueLabs, Inc.

Data Scientist

Washington, DC · On-site +1

Collaborate with engineers, data scientists, program managers and external stakeholders to troubleshoot problems and proactively create solutions * Assist on research development projects and data ...

Venture Global LNG

Senior Data Scientist

Arlington, VA · On-site

The company's Louisiana-based export projects service the global demand for North American natural ... Ability to self-manage and make your own decisions. * Strong presentation skills to effectively ...

Venture Global LNG

Senior Data Scientist

Arlington, VA · On-site

The company's Louisiana-based export projects service the global demand for North American natural ... Ability to self-manage and make your own decisions. * Strong presentation skills to effectively ...

SAIC

Data Scientist

Springfield, VA · Remote

Data Scientist Schedule: Full-Time Shift: Day Job Travel: No Minimum Clearance Required: TS.SCI ... Collaborate with project requestors, stakeholders, and project managers to refine project requests ...

9th Way Insignia

Data Scientist

Washington, DC

The Data Scientist works closely with ETL Developers, Power BI Developers, Data Analysts, Power Apps Developers, Technical Project Managers, testers, technical writers, and Government stakeholders to ...

Cornerstone Defense

Data Scientist

Reston, VA · On-site

Data Scientist Location: Reston, Virginia *Clearance: *Active TS/SCI w/ Polygraph needed to apply ... Collaborate with the Client project manager, technical analysts, and customer end-users in the ...

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Data Scientist Project Manager information

See Reston, VA salary details

$47.9K

$171.7K

$253.3K

How much do data scientist project manager jobs pay per year?

As of May 28, 2026, the average yearly pay for data scientist project manager in Reston, VA is $171,677.00, according to ZipRecruiter salary data. Most workers in this role earn between $138,900.00 and $176,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Scientist Project Manager, and why are they important?

To thrive as a Data Scientist Project Manager, you need a solid background in data science, analytics, and project management, often supported by degrees in computer science, statistics, or business and certifications like PMP or Agile. Familiarity with tools such as Python, R, SQL, project management software (e.g., Jira, Trello), and cloud platforms is crucial. Excellent communication, leadership, and problem-solving abilities help bridge gaps between technical teams and stakeholders. These skills ensure successful project delivery by aligning data-driven insights with business objectives and effective team coordination.

How do Data Scientist Project Managers typically balance technical data work with project management responsibilities?

Data Scientist Project Managers often split their time between hands-on data analysis and overseeing project progress. They commonly coordinate with cross-functional teams, set project timelines, and ensure that data solutions align with business objectives while occasionally contributing code or analytical insights. Effective communication and time management are essential, as they must bridge the gap between technical teams and stakeholders. This dual responsibility offers exposure to both technical growth and leadership development, making it ideal for professionals seeking advancement into higher management roles.

What is a Data Scientist Project Manager?

A Data Scientist Project Manager is a professional who oversees data science projects from conception through completion, ensuring that project goals align with business objectives. They bridge the gap between data science teams and stakeholders, managing timelines, resources, and communication. In addition to technical knowledge in data science and analytics, they possess strong project management skills to coordinate tasks, mitigate risks, and deliver results. Their role is essential for translating complex data-driven insights into actionable business strategies. They often use methodologies like Agile or Scrum to guide project workflows and adapt to changing requirements.

What is 90% of a project manager's job?

For a Data Scientist Project Manager, approximately 90% of the job involves planning, coordinating, and overseeing data science projects to ensure timely delivery and alignment with business goals. This includes managing teams, communicating with stakeholders, and utilizing project management tools like Agile or Scrum methodologies.

What is the difference between Data Scientist Project Manager vs Data Analyst Project Manager?

AspectData Scientist Project ManagerData Analyst Project Manager
Required CredentialsBachelor's/Master's in Data Science, Analytics, or related fields; certifications like PMP or AgileBachelor's in Data Analysis, Business, or related fields; certifications like PMP or Agile
Work EnvironmentLeads data science projects, collaborates with data scientists and engineersManages data analysis projects, works with analysts and business teams
Employer & Industry UsageTech companies, finance, healthcare, industries with advanced analyticsRetail, marketing, finance, industries relying on data reporting

The main difference is that Data Scientist Project Managers oversee data science initiatives involving complex modeling and algorithms, while Data Analyst Project Managers focus on managing data reporting and analysis projects. Both roles require project management skills and relevant certifications, but their technical focus and team collaboration differ.

What are popular job titles related to Data Scientist Project Manager jobs in Reston, VA? For Data Scientist Project Manager jobs in Reston, VA, the most frequently searched job titles are:
What job categories do people searching Data Scientist Project Manager jobs in Reston, VA look for? The top searched job categories for Data Scientist Project Manager jobs in Reston, VA are:
What cities near Reston, VA are hiring for Data Scientist Project Manager jobs? Cities near Reston, VA with the most Data Scientist Project Manager job openings:
Data Scientist Project Manager jobs near you
Data Scientist

Data Scientist

JS Consulting

Washington, DC • On-site

Contractor

Posted 16 days ago

Job description

Job Title- Data Scientist

Project Location – Onsite in Washington, District of Columbia

Duration- 6+ months contract

Visa- USC

Must have PHD

 Minimum Qualifications:

  • Work or educational background in one or more of the following areas: machine learning, computational linguistics, deep learning, ratification intelligence, data science and/or data analytic, generative AI, symbolic AI, causal AI, operations research, computer science, Mathematics, business analytics, or knowledge management.
  • Demonstrated experience programming with R/Python, Linux, and Spark in AWS cloud environment, or knowledge and algorithmic design experience in Python (3+ years)
  • Proficient with Amazon AWS Sagemaker, Jupyter Notebook and Python Scikit, Deep Learning, Machine Learning tools such as TensorFlow
  • Experience with image processing models such as Coco, CLIP, ResNet or comparable models
  • Demonstrated experience with machine learning techniques including natural language processing, and Large language Models (GPTv4-o1, o3, OpenAI APIs, Llama, Claude, etc).
  • Experience developing AI agents and development proficiency using agentic programming
  • Proficient in Natural language processing (NLP) and Natural language generation (NLG) including prior projects in any of the following categories: top modeling of text, sentiment analysis of text, part of speech tagging, Name Entity Recognition (NER), Bag of Words, text extraction
  • Experience building and working with any of these components: Vector DB, BERT, RoBERTa (or comparable tools), Spacy, LLM and GenAI tools. Experience with LoRA, LangChain, RAG, LLM Fine Tuning and PEFT, Knowledge Graphs.
  • Strong skills in developing GraphRAG, Chain of Thought (CoT), Tree of Thought (ToT), Reinforcement learning and AI development architectures with Human-in-the-Loop (HITL
  • Demonstrated experience with SQL and any relational database technologies, such as Oracle, PostgreSQL, MySQL, RDS, Redshift, Hadoop EMR, Hive, etc.
  • Demonstrated experience processing structured and unstructured data sources, data cleansing, data normalization and prep for analysis
  • Demonstrated experience with code repositories and build/deployment pipelines, specifically Jenkins and/or Git/GitHub/GitLab.
  • Demonstrated experience using Tableau, or Kibana, Quicksights or other similar data visualizations tools.
  • Very comfortable working with ambiguity (e.g. imperfect data, loosely defined concepts, ideas, or goals)

 Qualifications & Requirements

  • Education: MS in Computer Science, Statistics, Math, Engineering, or related field, PhD required.
  • 3+ years of relevant experience in building large scale machine learning or deep learning models and/or systems
  • 1+ year of experience specifically with deep learning (e.g., CNN, RNN, LSTM)
  • 1+ year of experience building NLP and NLG tools.
  • Experience with wide range of LLMs (Llama, Claude, OpenAI, Cohere, etc.), LoRA, LangChain, RAG, LLM Fine Tuning and PEFT are preferred.
  • Demonstrated skills with Jupyter Notebook, AWS Sagemaker, or Domino Datalab or comparable environments
  • Passion for solving complex data problems and generating cross-functional solutions in a fast-paced environment
  • Knowledge in Python and SQL, object oriented programming, service oriented architectures
  • Strong scripting skills with Shell script and SQL
  • Strong coding skills and experience with Python (including SciPy, NumPy, and/or PySpark) and/or Scala.
  • Knowledge and implementation experience with NLP techniques (topic modeling, bag of words, text classification, TF/IDF, Sentiment analysis) and NLP technologies such as Python NLTK, or Spacy or comparable technologies
  • Knowledge and implementation experience with statistical and machine learning models (regression, classification, clustering, graph models, etc.)

 Preferred Qualifications

  • Hands on experience building models with deep learning frameworks like Tensorflow, Keras, Caffe, PyTorch, Theano, H2O, or similar
  • Experience with LLM Agents, Agentic programming
  • Experience with search architecture (for instance: Solr, ElasticSearch, AWS OpenSearch)
  • Experience with building querying ontologies such as Zeno, OWL, RDF, SparQL or comparable are preferred
  • Knowledge & experience with microservices, service mesh, API development and test automation are preferred
  • Demonstrated experience using Docker, Kubernetes, and/or other similar container frameworks are preferred

 Additional Job Qualifications:

  • Ability to translate business ideas into analytics models that have major business impact.
  • Demonstrated experience working with multiple stakeholders.
  • Demonstrated communication skills, e.g. explaining complex technical issues to more junior data scientists, in graphical, verbal, or written formats.
  • Demonstrated experience developing tested, reusable and reproducible work.