McLean, VA

Data Jobs in McLean, VA

168 jobs found

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Today

Principal Data Analyst

Information Technology Senior Management Forum McLean, VA

McLean, VA

Today

$131k - $150k/yr Full time Analytics Big Data Business Analytics

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Job Description

Lead the design and delivery of data solutions that enable self-service analytics, data quality governance, and business decision-making.

Responsibilities

Mine complex, high-volume, and varied data sources and platforms using Open Source and digital technologies
Build and maintain well-managed data solutions, tools, and capabilities that support self-service frameworks for data consumers
Rapidly learn and apply new technologies to advance multiple initiatives
Partner with the business to translate requirements into tools, techniques, metrics, and dashboards for insight and data visualization
Drive analysis that produces meaningful insights for business strategies
Support adoption of data quality management principles, including metadata, lineage, and business definitions
Collaborate with relevant Tech teams to manage security mechanisms and data access governance
Build and execute tools to monitor and report on data quality

Requirements

Degree specialized in a Science, Technology, Engineering, Mathematics discipline
Scripting experience with Python, R, Spark, and SQL
Experience working with data in various forms (data warehouses/SQL, unstructured data)
Experience using and developing within AWS services
Currently has, or is in the process of obtaining, a Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related quantitative field) plus at least 5 years of data analytics experience; or a Master’s Degree plus at least 3 years of data analytics experience, with expectation the required degree will be obtained on or before the scheduled start date
At least 3 years of experience working with one scripting language
At least 3 years of experience using a business intelligence visualization tool
At least 3 years of experience querying, analyzing, and working with data languages and platforms

Technologies

Python, R, Spark, SQL
AWS services
Snowflake/Onelake
Databricks

Preferred Qualifications

Master’s Degree in a Science, Technology, Engineering, Mathematics discipline
At least 4 years of experience coding in Python, R, Spark, or SQL
At least 4 years of experience with process management and improvement methodologies (Agile, Lean, Six Sigma, etc.)
At least 2 years of experience using and developing within AWS services
At least 2 years delivering Data Governance and Data Quality Management concepts and practices within the financial services industry
Capital One may sponsor a new qualified applicant for employment authorization for this position

Location and Work Mode

McLean, VA (hybrid)
Designated as a hybrid role; must follow Capital One’s hybrid policy for required on-site presence at the designated office location

Compensation

Annual salary range (McLean, VA): $131,300 - $149,800 for Principal Data Analyst
Annual salary range (New York, NY): $143,200 - $163,500 for Principal Data Analyst
Annual salary range (Richmond, VA): $119,400 - $136,200 for Principal Data Analyst
Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)

Benefits

Health, financial, and other benefits that support total well-being

Application

Expected to accept applications for a minimum of 5 business days

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Today

Data Engineer, Senior

Booz Allen Hamilton McLean, VA

McLean, VA

Today

$78k - $176k/yr Full time Senior Amazon Web Services AWS

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Job Description

Build mission-critical data pipelines at Booz Allen Hamilton in McLean, VA (onsite), delivering scalable cloud-based data workflows that support analytics and enterprise applications. This Senior Data Engineer role combines hands-on engineering with Agile practices and strong platform ownership, backed by a comprehensive benefits package including health, retirement, and professional development support.

What you’ll do

Design, develop, test, and maintain scalable data pipelines and data processing workflows.
Build and optimize data solutions using Databricks, including data transformation, processing, and orchestration.
Create automated workflows that improve reliability, efficiency, and repeatability of data processing.
Integrate data from multiple sources and formats into enterprise data platforms.
Develop and optimize data transformations using SQL and Python.
Troubleshoot data pipeline issues, then identify opportunities to improve performance and reliability.
Collaborate with software developers, data engineers, architects, and stakeholders to understand requirements and deliver technical solutions.
Apply Agile development practices, version control, testing, and CI/CD across the software development lifecycle.

What you’ll need

5+ years of experience in data engineering, database development, or data warehousing.
Strong SQL experience including complex queries, joins and aggregations, CTEs, window functions, query optimization, and performance tuning, plus relational database development, troubleshooting, and performance tuning.
Experience developing and maintaining data pipelines using Python, and Apache Spark or PySpark for processing and transforming large datasets, including performance optimization and troubleshooting.
Experience with Databricks as a data engineering platform.
Experience with Amazon Web Services (AWS) and AWS data services such as S3, EMR, Glue, Lambda, or NoSQL databases.
Experience with CI/CD pipelines, including using GitHub Actions for automated builds, testing, deployment, and environment promotion.
Knowledge of database design principles and data warehousing concepts, including ETL/ELT, fact and dimension tables, star and snowflake schemas, slowly changing dimensions, data integration, and incremental data processing.
Ability to independently troubleshoot pipeline failures, data issues, performance problems, and production incidents, including determining root causes and corrective actions.
Public Trust and a Bachelor’s degree in Computer Science.
U.S. citizenship is required.

Technologies you’ll work with

Databricks, AWS (S3, EMR, Glue, Lambda), SQL, Python, Apache Spark, PySpark
NoSQL databases
GitHub Actions

Benefits

Health, life, disability, financial, and retirement benefits
Paid leave
Professional development
Tuition assistance
Work-life programs
Dependent care
Recognition awards program

Nice to have

Experience with data lake or Lakehouse architectures
Experience with DevSecOps practices
Experience working in federal or other highly regulated environments
Knowledge of data modeling (conceptual, logical, and physical), dimensional modeling, and designing models for analytics and reporting
Ability to contribute to technical design and architecture discussions, evaluate implementation approaches, and develop scalable, maintainable, reliable data engineering solutions
Ability to use AI-assisted development tools for productivity, code generation and review, troubleshooting, SQL and Spark optimization, documentation, and accelerated learning while following organizational security and data-protection standards

Vetting and identity verification

Selected applicants will be subject to a government investigation and may need to meet U.S. government eligibility requirements; Public Trust determination is required.
During the hiring process, you will complete an identity verification process using advanced biometrics and AI to ensure authenticity and protect against identity fraud.
You may be expected to be on camera during interviews and assessments, and the company may take your picture to verify identity and prevent fraud.

Compensation

Projected compensation range: $77,600 to $176,000 per year (annualized USD).

Work model

Onsite: Work will primarily be performed full-time at a customer facility, with collaboration directly with colleagues and customers as required by the role. Employees working virtually are generally expected to have cameras on during meetings.

Candidate AI usage policy

Use of artificial intelligence or other tools to assist with responses during interviews (in-person or virtual) is prohibited unless permission is explicitly provided.

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1d ago

Machine Learning Engineer 5, Senior Manager - Intelligent Foundations and Experiences (IFX)

Information Technology Senior Management Forum McLean, VA

McLean, VA

1d ago

$230k - $262k/yr Full time Backend Developer Manager Ai Ml

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Job Description

In this senior leadership Machine Learning Engineer role, you will help design and scale AI and machine learning capabilities, from model development through production training and monitoring. The position supports Capital One-focused implementation work and involves building multi-tenant ML platforms alongside Product and Data Science teams.

This onsite role is based in McLean, VA and targets candidates with strong experience across ML modeling, distributed data systems, and cloud deployment practices.

Role focus

Design, build, and deliver ML models and components to address business problems in collaboration with Product and Data Science teams
Build and scale large multi-tenant platforms for ML model training and serving at scale
Use ML modeling knowledge to guide infrastructure decisions, including model choice, data and feature selection, training approach, hyperparameter tuning, dimensionality, and bias/variance tradeoffs and validation
Solve complex engineering problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Retrain, maintain, and monitor models in production
Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
Construct optimized data pipelines that feed ML models
Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to support successful deployment of ML models and application code
Maintain well-managed code to reduce vulnerabilities, ensure risk-governed model usage, and follow best practices in Responsible and Explainable AI
Work within an Agile, cross-functional team to create and enhance software enabling big data and ML applications

Programming and tooling

Use Python, Scala, or Java for development
Technologies include PyTorch, Tensorflow, Pandas, NumPy, Scikit-learn
Distributed systems for data preparation include Spark and Ray
Cloud and orchestration: AWS, GCP, Azure, and Kubernetes
CI/CD practices are expected for deployment workflows

Minimum qualifications

Bachelor’s degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 6 years of experience programming with Python, Java, Golang, or C++
At least 6 years of Machine Learning experience using PyTorch or Tensorflow and libraries such as Pandas, NumPy, and Scikit-learn
At least 6 years using and operating large scale distributed systems like Spark and Ray for AI or ML data preparation
At least 4 years deploying and operating ML solutions in production, operating production services in the cloud (AWS, GCP, Azure), and using Kubernetes to manage large scale containerized ML systems

Preferred qualifications

Master’s or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field
+2 years experience building production RAG pipelines (chunking, embeddings, vector indexing, graph RAG, or fine-tuning)
+2 years experience leveraging agentic patterns (Tool Calling, ReAct loops, Plan-and-Execute, Multi-Agent Collaboration)
+2 years with LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel) and model APIs (OpenAI, Anthropic, Bedrock, Ollama, Hugging Face)
+2 years of experience building agentic AI systems and agentic workflows
+2 years developing AI and ML algorithms or technologies (e.g., LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang
+2 years experience right-sizing models, instance counts, and hardware types based on requirements (context length, token inputs, token outputs)
5+ years optimizing ML algorithms, configurations, and infrastructure
5+ years following software development best practices including source control, testing, code reviews, and CI/CD
5+ years building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and incident response planning
5+ years working with ML techniques (Supervised, semi-supervised, and unsupervised learning, reinforcement learning) and model types (Regression, Classification, Clustering)
5+ years with model architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and evaluating model accuracy
5+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
Ability to communicate complex technical and machine learning concepts to a variety of audiences

Compensation and benefits

Salary: USD 229,900 - 262,400 per year for the McLean, VA location (Machine Learning Engineer 5)
Salary: USD 209,000 - 238,500 per year for Richmond, VA (Machine Learning Engineer 5)
Eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI)
Capital One offers comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being

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1d ago

Machine Learning Engineer 5, Senior Manager - Intelligent Foundations and Experiences (IFX)

Capital One McLean, VA

McLean, VA

1d ago

$230k - $262k/yr Full time Manager Artificial Intelligence Big Data

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Job Description

Capital One is seeking a Senior Manager-level Machine Learning Engineer to design, build, and scale machine learning models and platforms that support real-world business needs. The role focuses on ML infrastructure, production data pipelines, and responsible and explainable AI across cloud environments.

Responsibilities

Design, build, and/or deliver ML models and components that address real-world business problems in collaboration with Product and Data Science teams.
Build and scale multi-tenant platforms that support large footprint ML training and/or serving at scale.
Guide ML infrastructure decisions using expertise across model selection and data and feature selection, including training, hyperparameter tuning, dimensionality, bias/variance, and validation.
Develop and validate ML models and application code, including automated testing and deployment.
Collaborate within a cross-functional Agile team to create and enhance software for big data and ML applications.
Retrain, maintain, and monitor models in production.
Leverage and/or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply CI/CD best practices, including test automation and monitoring, to support successful deployment of ML models and application code.
Ensure code is well-managed to reduce vulnerabilities; support risk-governed model practices and follow Responsible and Explainable AI best practices.
Use programming languages such as Python, Scala, or Java.

Requirements

Bachelor’s Degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
At least 6 years of experience programming with Python, Java, Golang, or C++.
At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or TensorFlow, and libraries including Pandas, NumPy, and Scikit-learn.
At least 6 years of experience operating large-scale distributed systems such as Spark and Ray to prepare AI and Machine Learning data.
At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure), including using Kubernetes to manage large-scale containerized ML software systems.

Preferred Qualifications

Master’s or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
+2 years experience building production RAG pipelines (chunking, embeddings, vector indexing, graph RAG, or fine-tuning).
+2 years experience leveraging agentic patterns (Tool Calling, ReAct loops, Plan-and-Execute, Multi-Agent Collaboration).
+2 years with LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel) and model APIs (OpenAI, Anthropic, Bedrock, Ollama, Hugging Face).
+2 years of experience building agentic AI systems and agentic workflows.
+2 years developing AI and ML algorithms or technologies (for example, LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang.
+2 years experience right-sizing models, instance counts, and hardware types given requirements (for example, context length, token inputs, token outputs).
5+ years of experience optimizing ML algorithms, configurations, and infrastructure.
5+ years following software development best practices including source control, testing, code reviews, and CI/CD.
5+ years building resilient software with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring and alarms, and preparing incident response plans.
5+ years working with machine learning techniques (supervised, semi-supervised, unsupervised, reinforcement learning) and model types (regression, classification, clustering), including architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and evaluating accuracy and diagnosing issues (underfitting, overfitting).
5+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences.

Technology Stack

Python, Scala, Java, Golang, C++
PyTorch, TensorFlow, Pandas, NumPy, Scikit-learn
Spark, Ray
AWS, GCP, Azure, Kubernetes

Benefits

Performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
Comprehensive, competitive, and inclusive set of health, financial, and other benefits to support total well-being.

Compensation and Location

Location: McLean, VA (onsite)

Salary: USD 229,900 - 262,400 per year

Salary information: McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5; Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5

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4d ago

Senior AI Engineer

The MITRE Corporation McLean, VA

McLean, VA

4d ago

$144k - $215k/yr Full time Senior Artificial Intelligence Artificial Intelligence Engineer

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Job Description

The Mitre Corporation is seeking a Senior AI Engineer to develop, evaluate, and clearly communicate results for Artificial Intelligence and Machine Learning solutions. This role emphasizes hands-on work, rapid prototyping, and the ability to tackle complex technical problems while sharing advanced knowledge across the team. The position is based in McLean, VA (onsite).

Salary range: USD 143,600 - 215,400 per year (midpoint: $179,500). Experience: typically 5+ years in a related field.

What you’ll do

Rapidly prototype and evaluate AI/ML approaches to determine feasibility and support project needs.
Lead simple projects or take accountability for tasks within complex programs, including planning and guiding others’ work.
When operating as a contributor, work independently with minimal instruction and direction.
Identify and resolve complex problems, applying new perspectives to existing solutions and using judgment across Data Science and AI.
Leverage advanced expertise in Data Science and Artificial Intelligence and share knowledge with others.
Communicate complex results through writing and verbal updates for both technical and non-technical audiences.

Required qualifications

Typically a minimum of 5 years of related experience with a Bachelor’s; or 3 years with a Master’s; or a PhD with relevant experience who can contribute immediately; or an equivalent combination of education and experience.
Hands-on proficiency in AI/Data Science techniques including Large Language Models, Natural Language Processing, Computer Vision, and other ML approaches such as supervised, unsupervised, deep learning, and reinforcement learning.
Computer programming skills in one or more languages such as Python, C/C++, Java, Scala, Julia, Rust.
Security clearance: must have an active Top Secret/SCI with polygraph. U.S. citizenship is required to be considered for a security clearance.
On-site requirement: minimum 3 days per week.

Technical focus areas

The role spans a broad set of AI and data capabilities, including:

Machine Learning and model evaluation
Large Language Models and techniques such as Prompt Engineering, Few-Shot Learning, Retrieval Augmented Generation (RAG), and LLM fine-tuning and hosting
Agentic AI frameworks and approaches
DevOps for AI
Computer Vision topics such as object detection, image classification, and diffusion models
Natural Language Processing including encoders, summarization, classification, entity recognition, and topic modeling
Databases across SQL, NoSQL, vector, and graph systems
Data engineering for distributed processing and orchestration (for example Spark, Hadoop, Ray, Dask, Kafka, Airflow, Dagster, and NiFi)
MLOps practices such as model deployment, monitoring, reproducibility, and containerization

Preferred qualifications

Master’s degree in Computer Science, Mathematics, Applied Mathematics, Data Science, or a related field with 3 years of relevant experience.
Alternatively, a PhD in a related field.

Clearance requirements

Candidate must have a minimum clearance of: Top Secret/SCI/Polygraph.
Candidate must have or obtain within one year from the date of hire: Top Secret/SCI/Polygraph.

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7d ago

Machine Learning Engineer

Dezign Concepts LLC McLean, VA

McLean, VA

7d ago

Up to $190k/yr Full time Python Ai Ml Artificial Intelligence

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Job Description

This role applies machine learning and NLP techniques to develop and adapt Large Language Models (LLMs) that improve analytic workflows and help answer intelligence questions using both structured and unstructured data. The position includes building models, analytics, ETL pipelines, and reports in a team setting.

Key Responsibilities

Leverage open source, best-in-class models to create reusable and repurposable model artifacts using fine-tuning, transfer learning, and ensembles, including domains such as classification.
Develop supervised model approaches using open source architectures such as CNN, Unet, YOLO, or similar.
Create unsupervised approaches using methods such as DBSCAN, K-Nearest, Adaboost, or similar.
Build prediction-oriented models, including predictors such as LSTM, UConv, or similar.
Develop regressors including Bayesian, linear, or similar.
Implement fusion approaches at the sensor level and entity level.
Support decision-making model development, including task assignments, combinational and parametric optimizations, reinforcement learning, path planning, or similar.
Develop generative model solutions, including LLMs and stackable LLM approaches, using fine-tuning, transfer learning, and ensembles.
Apply AI/ML, deep learning, NLP, recommendation, threat detection, computer vision, data mining, statistics, and related methods using appropriate frameworks such as TensorFlow and PyTorch.
Analyze large volumes of raw data, including text, to determine suitability for training or testing AI models.
Preprocess and clean structured and unstructured sponsor data, including text data.
Design and implement advanced ETL code and table configurations for complex data sets.
Use SQL to develop and organize relevant information.
Collaborate with the team to author analytic publications and produce ad-hoc reports with data visualizations aligned to sponsor templates; document methods in GitHub.
Implement the sponsor’s existing coordination process.
Provide ad-hoc technical education to staff.
Deliver subject matter expertise in AI/ML to support sponsor initiatives.

Required Qualifications

Citizenship: Must be a US Citizen.
Education: Minimum Bachelor’s Degree required.
Security clearance: Active Top Secret SCI with Poly required.
Experience: Expert level experience required.
Demonstrated experience tuning neural networks, such as LLMs, on custom datasets and applying results to specific use cases.
Demonstrated professional or academic experience using Python or R.
(KEY) Demonstrated experience developing models and ensembles in the AI/ML space, including selecting Python libraries, choosing pre-processing actions, performing analysis, and assessing model performance.
(KEY) Demonstrated professional or academic experience testing, evaluating, or validating AI systems performance, with a focus on LLM-based systems.
(KEY) Demonstrated professional or academic experience in experiment design and execution to benchmark LLM performance.
(KEY) Demonstrated professional or academic experience with deep learning frameworks such as PyTorch, TensorFlow, or Keras.
(KEY) Demonstrated professional or academic experience and proficiency with SQL, including common table expressions, set operations, aggregated functions, and nested subqueries.
(KEY) Demonstrated experience leveraging GPUs for accelerated computing.
Demonstrated professional or academic experience with version control systems such as GitHub and Jenkins.

Technology Stack

Python, R, SQL
TensorFlow, PyTorch, Keras
CNN, Unet, YOLO
DBSCAN, K-Nearest, Adaboost
LSTM, UConv, Bayesian
Reinforcement Learning, Path Planning
LLMs, Stackable LLMs
GitHub, Jenkins
GPUs, HuggingFace Transformers library, HuggingFace hub
Flask, SciKit Learn, Tableau, ONNX

Benefits

Medical, Dental, Vision, Health Savings Account and more.
Paid Time Off, Holidays, Social Events, Employee Assistance Program and Team Building.
401K, Tuition Assistance, Annual and Referral Bonuses.

Security Clearance Note

Active Top Secret Clearance with Poly Required.
Please note: this job requires an existing Top Secret Clearance and Polygraph.

Travel

Local travel/POV will be on an as needed basis, within the local place of performance.

Highly Desired (Not Required)

Demonstrated experience with the HuggingFace Transformers library and hub.
Demonstrated experience with cloud computing development and architecture.
Demonstrated experience with front-end web development frameworks such as Flask.
Demonstrated experience creating machine learning models for text classification and topic modeling in Python using standard machine learning (SciKit Learn) or deep learning models.
Demonstrated experience developing applications for semantic search.
Proficiency with Tableau to produce visualizations and dashboards.
Experience communicating methodological choices and model results.
Demonstrated experience with verification and validation test benches.
Demonstrated experience with Explainable AI (XAI) techniques.
Demonstrated experience with ONNX (Open Neural Net Exchange).

Location and Salary

Location: McLean, VA (onsite).

Salary: USD 190,000 per year (salary is commensurate with education and experience; up to $190K).

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10d ago

Financial Management Data Engineer

Guidehouse Inc. McLean, VA

McLean, VA

10d ago

$113k - $188k/yr Full time Analytics Automation Developer Big Data

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Job Description

Guidehouse is seeking a Financial Management Data Engineer to collect, transform, integrate, and analyze data in support of DHS Financial Management mission goals and decision-making. This onsite role in McLean, VA focuses on building data ingestion and integration capabilities, applying analytics and predictive approaches, and maintaining data governance and quality for client deliverables.

Responsibilities

Access data sources by establishing connections and developing data ingestion and integration solutions using APIs, databases, file-based interfaces, and enterprise platforms to support data acquisition and pre-processing for analysis.
Aggregate, clean, and organize datasets from disparate sources, including quality assurance of these processes.
Design and implement data integration, mapping, and standardization frameworks with configurable business rules and data crosswalks to support interoperability, reconciliation, and reporting across financial and operational systems.
Manipulate large data sets, perform data mining, and structure raw data using open-source tools such as SQL, Python, and PySpark to identify patterns that generate new information and insights for decision support.
Develop data modeling processes and apply algorithms, predictive models, and ad hoc or exploratory data analysis, including advanced analytics techniques such as predictive modeling and machine learning.
Ensure data governance and quality assurance standards are met.
Help define data quality metrics tied to the quality of data ingested into Databricks.
Organize and lead client meetings, including scheduling, drafting and delivering agendas and meeting minutes, archiving required documentation, and documenting, tracking, and following up on action items.
Deliver client services and support business development, internal firm initiatives, and ongoing professional development.

Requirements

Ability to obtain and maintain a Federal or DoD “PUBLIC TRUST”; candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred.
Bachelor's degree.
Three (3) or more years of data experience.
Experience performing data analytics to address management and operational challenges.
Proficiency with data analytic tools including SQL, Python, R, and Databricks.
Proficiency in Microsoft Suite, with emphasis on MS PowerPoint, MS Word, and MS Excel.
Prior experience with statistical analysis, predictive modelling, machine learning, and artificial intelligence.

Technologies

SQL, Python, PySpark, Databricks
R
Microsoft PowerPoint, Microsoft Word, Microsoft Excel, Power BI
Power Apps, Power Automate, SharePoint, Microsoft Power Platform, Microsoft Suite
MicrosoftAzure, AWS
APIs, databases, file-based interfaces, enterprise platforms

Benefits

Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Position may be eligible for a discretionary variable incentive bonus
Parental Leave and Adoption Assistance
401(k) Retirement Plan
Basic Life & Supplemental Life
Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
Short-Term & Long-Term Disability
Student Loan PayDown
Tuition Reimbursement, Personal Development & Learning Opportunities
Skills Development & Certifications
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Emergency Back-Up Childcare Program
Mobility Stipend

Additional Details

Location: McLean, VA 22102 (onsite)
Salary range: USD 113,000 - 188,000 per year
Travel required: Up to 10%
Clearance required: Ability to Obtain Public Trust

What Would Be Nice to Have

Experience collaborating in a team environment and working independently.
Ability to identify and address client needs, build relationships, prioritize tasks, and communicate potential conflicts to a supervisor.
Professional communication skills across audiences, including management levels and external clients.
Experience facilitating meetings and presenting topics to diverse functional and technical staff.
Experience in commercial or public sector consulting firms.
Prior experience supporting federal finance organizations.
Experience with cloud-based platforms and services, including MicrosoftAzure, AWS, or similar cloud environments.
Experience with Microsoft Power Platform tools (Power BI, Power Apps, Power Automate) and SharePoint.

WHAT WOULD BE NICE TO HAVE

Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package aligned with creating a diverse and supportive workplace.