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2mo ago

IT & Data Analyst

U.S. Army Seattle, WA

Seattle, WA

2mo ago Closed

Full time Data Analysis Data Analytics Reporting and Analytics

This position is no longer accepting applications (closed Sep 27, 2026).

Job Description

The U.S. Army is seeking an IT & Data Analyst in Seattle, WA for onsite work. In this role, you will gather, organize, analyze, and share critical information to support planning and operations in complex, fast-moving situations. The work centers on reviewing data from multiple sources, spotting patterns and risks, and producing clear reports and accurate records.

What you’ll do

Gather, organize, analyze, and share important information so teams can make informed decisions in complex situations
Review data from multiple sources
Identify patterns and risks in the information you assess
Prepare reports based on your analysis
Maintain accurate records that support planning and operational needs
Build practical experience in research, data analysis, critical thinking, documentation, information management, and communicating findings clearly to support decision-making

Related role overview

35F – Intelligence Analyst (example role category): the work includes reviewing data from multiple sources, identifying patterns and risks, preparing reports, and maintaining accurate records for planning and operations

Service requirement and placement context

This job requires military service under a contract for enlistment or commission. It is not an application to a specific position within the military; it is an example of a role you could be placed into after taking a job placement exam.

Enlistment steps include speaking with a recruiter, taking a job placement exam, completing a physical exam, selecting from presented career options, signing a career contract of 2 to 6 years, taking the oath of enlistment, and attending bootcamp

Requirements

Age between 17 and 42
Medically and physically fit
U.S. citizen or permanent resident with a valid Green Card
High school diploma or equivalent

Skills you will develop

Research and information gathering
Data analysis and pattern recognition
Critical thinking and analytical reasoning
Report writing and documentation
Records management and file organization
Risk assessment and situational analysis
Cross-referencing and information verification
Attention to detail and accuracy
Clear communication of findings
Supporting operational and strategic decision-making

Certifications and job type

24 Nationally-Recognized Certifications Available
Full-Time
Part-Time

Benefits

Dental insurance
Employee assistance program
Health insurance
Life insurance
Professional development assistance
Tuition reimbursement
Vision insurance

Location and work setup

Seattle, WA (onsite)
Work location: On the road

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2mo ago

Data Analyst

Sedgwick Miami, FL

Miami, FL

2mo ago Closed

Full time Data Analysis Data Analytics Data Processing

This position is no longer accepting applications (closed Sep 27, 2026).

Job Description

Use statistical reporting and data integrity practices to support performance initiatives in an onsite Florida role.

Responsibilities

Compile data, prepare and distribute reports, and analyze results
Support efficient program management by identifying trends in work quality and cost effectiveness
Analyze and compile data derived from technical reviews, as applicable, in coordination with relevant staff
Provide training and coaching focused on processing and procedure issues
Deliver trend analysis and ongoing reporting based on statistical findings
Ensure data integrity by developing and producing reports used to measure data accuracy
Extract data and analyze information aligned to plan and jurisdictional requirements
Gather and prepare statistical data for reporting and provide recommendations to management regarding training needs
May analyze cause-and-effect ratios, return-to-work and accommodations trending, disability durations, injury by job type analysis, and disability diagnosis trending
Present findings to clients and/or management
May assist with completion of client set-up and maintenance (parameter) forms
Support organizational quality program(s)
Perform other duties as assigned
Travel as required

Requirements

Bachelor’s degree with a major in Computer Science, Finance, or Economics from an accredited college or university (preferred)
Six (6) years of related experience, or an equivalent combination of education and experience required
Three (3) years of query and report writing strongly preferred
Thorough knowledge of query and report writing
Excellent oral and written communication, including presentation skills
PC literate, including Microsoft Office products
Strong analytical and interpretive skills
Strong organizational skills
Excellent interpersonal skills
Ability to work effectively in a team environment
Ability to meet or exceed Performance Competencies
Credit security clearance, confirmed via a background credit check, is required for this position

Work Environment

Reasonable accommodations will be considered when applicable and appropriate

Work Skills (Mental)

Clear and conceptual thinking ability
Excellent judgment, troubleshooting, problem solving, analysis, and discretion
Ability to handle work-related stress
Ability to handle multiple priorities simultaneously
Ability to meet deadlines

Work Skills (Physical)

Computer keyboarding
Travel as required

Work Skills (Auditory/Visual)

Hearing, vision, and talking

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2mo ago

Data Analyst

Apple Austin, TX

Austin, TX

2mo ago Closed

Full time Analytics Artificial Intelligence Bi Tools

This position is no longer accepting applications (closed Sep 27, 2026).

Job Description

Data Analyst opportunity in the Satellite Connectivity Group at Apple, based in Austin, TX (onsite).

Responsibilities

Collaborate with cross-functional teams to understand the system end-to-end, analyze key metrics, and address questions about performance and user experience.
Mine and synthesize data from multiple sources, using statistical methods and machine learning to identify trends, anomalies, and actionable insights.
Build and maintain data pipelines that enable reliable, repeatable analysis.
Create visualizations, dashboards, and reports that clearly communicate results to both technical and non-technical audiences.
Convert complex findings into simple, compelling narratives that motivate action and drive improvements.
Investigate anomalies and performance issues to determine root causes and recommend solutions.

Requirements

Minimum: 3+ years of experience with data analysis and reporting.
Minimum: Experience synthesizing complex data sources into clear, insightful presentations with an emphasis on the story.
Minimum: Demonstrated experience building analytic tools and analyzing operational data, then distilling results into actionable recommendations.
Minimum: Solid statistical concepts and machine learning algorithm knowledge.
Minimum: Excellent problem-solving skills and ability to work independently.
Minimum: Creativity and willingness to explore new solutions and ideas.
Minimum: Excellent data visualization skills.
Minimum: Proficiency with scripting languages such as Python, R, or MATLAB.
Minimum: Experience with databases and query languages such as SQL.
Minimum: Comfortable working across multiple languages and tools.
Minimum: Excellent written and verbal communication skills, with demonstrated teamwork and leadership skills.
Education: BS or MS in a quantitative field.
Quantitative fields include: data science, statistics, applied mathematics, operations research, engineering, or a related discipline.
Preferred: Familiarity with using AI to improve efficiency.
Preferred: Experience with BI and visualization tools.

Tech Stack

Python, R, MATLAB
SQL
BI and visualization tools
Machine learning, AI

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2mo ago

Geophysical Data Analyst

Bright Star Solutions LLC Washington, DC

Washington, DC

2mo ago Closed

$120k - $140k/yr Full time Data Analysis Data Analytics Data Pipeline

This position is no longer accepting applications (closed Sep 27, 2026).

Job Description

Bright Star Solutions LLC is hiring a Geophysical Data Analyst for a full-time hybrid role supporting a federal sensor technology program. In this position, you will process and interpret geophysical sensing data, apply signal processing and analytics to detection and anomaly detection workflows, and communicate results to both technical and non-technical stakeholders.

Role overview

You will work with data from geophysical sensing systems, including seismic, acoustic, and electromagnetic sources. The work centers on transforming raw sensor outputs into structured datasets, applying noise reduction and signal processing, and supporting interpretation efforts using statistical and data science approaches. You will also collaborate with engineers, scientists, and federal clients to refine how data is collected and analyzed.

Responsibilities

Process and analyze data from geophysical sensing systems, including seismic, acoustic, and electromagnetic sensors
Conduct signal processing and noise reduction to support detection and characterization workflows
Develop and maintain data pipelines for ingesting, cleaning, and structuring sensor datasets
Create visualizations, dashboards, and reports to communicate findings to technical and non-technical stakeholders
Support geophysical data interpretation and anomaly detection using statistical and data science approaches
Collaborate with engineers, scientists, and federal clients to improve data collection and analysis methods

Required qualifications

Bachelor’s degree in Geophysics, Physics, Earth Science, Data Science, Computer Science, Mathematics, Engineering, or a related field
2+ years of experience working with sensor or geophysical data in an applied setting
Proficiency in a scripting language or tool for data processing and analysis
Familiarity with signal processing concepts such as filtering, spectral analysis, and time-series analysis
Experience with data visualization tools, such as Matplotlib, Plotly, or Tableau
Ability to obtain and maintain a federal background investigation
Strong written and verbal communication skills, including comfort presenting findings to stakeholders
US citizen
Must currently hold an active DHS Public Trust or CBP Background Investigation (BI) (required qualification)

Technologies

Matplotlib, Plotly, Tableau
Python, SQL, Excel
SeisWare, OpendTect, Kingdom

Preferred qualifications

Experience with seismic, acoustic, or ground-penetrating radar (GPR) data
Proficiency in Python, SQL, and/or Excel for data analysis and reporting
Familiarity with geophysical processing software such as SeisWare, OpendTect, or Kingdom
Experience supporting federal government programs or defense/security contractors
Knowledge of machine learning techniques applied to sensor data classification or anomaly detection
Active DHS or CBP Background Investigation

Job details

Job type: Full-time
Salary: USD 120,000 - 140,000 per year
Work location: Hybrid remote in Washington, DC 20004
Preferred location: Sterling, VA (Ability to commute and relocate before starting work are listed as preferred)

Benefits

401(k) with matching
Health insurance
Dental insurance
Vision insurance
Disability insurance
Paid time off

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2mo ago

Machine Learning Engineer- Senior Consultant Level

Visa Technology and Operations LLC Austin, TX

Austin, TX

2mo ago Closed

$173k - $277k/yr Full time Python Senior Artificial Intelligence

This position is no longer accepting applications (closed Sep 27, 2026).

Job Description

Join Visa Technology and Operations LLC to design and deliver machine learning systems that improve performance, accuracy, and data management.

Responsibilities

Develop and program integrated software algorithms for product and systems applications in structured and unstructured environments
Use machine language and statistical modeling techniques to enhance performance, quality, data management, and accuracy
Perform rigorous validation and detect logical flaws using established machine learning practices
Translate algorithms and technical specifications into production code using current programming languages and technologies
Design and implement adaptive learning approaches, including model validation and A/B testing
Implement explainability methods to support understanding of model decisions

Requirements

8+ years of relevant work experience with a Bachelor Degree, or 5+ years with an Advanced Degree (e.g., Masters, MBA, JD, MD), or 2+ years with a PhD
Experience developing and programming integrated software algorithms for structured and unstructured data environments
Ability to program in one or more scripting languages such as Rust or Python, and one or more programming languages such as Java, C++, or C#
Advanced Generative AI experience/usage

Technologies

Rust, Python, Java, C++, C#, ChatGPT, Microsoft Copilot
TensorFlow, SAS, R, KNIME, Matlab
Generative AI tools
Decision trees, logistic regression, Bayesian analysis, Naïve Bayes, SVM, neural networks

Preferred Qualifications

9+ years relevant work experience with a Bachelor Degree, or 7+ years with an Advanced Degree, or 3+ years with a PhD
Bachelor’s Degree in Computer Science, Operations Research, Statistics, or a highly quantitative field (or equivalent experience) with strength in Deep Learning, Machine Learning, Data Mining, and statistical or mathematical analysis
Experience applying statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis, and others
Experience conducting rigorous validation and identifying logical flaws in machine learning solutions
Experience translating algorithms and technical specifications into code using current programming languages and technologies
Experience designing and implementing adaptive learning methods, model validation, and A/B testing
Experience explaining model decisions and ensuring post-deployment integrity and accuracy
Experience working with large datasets and modern big data and ML/AI technologies
Experience with relevant coursework in modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks
Experience with one or more statistical tools such as SAS, R, KNIME, or Matlab
Deep learning experience with TensorFlow (plus)

Benefits

Medical, Dental, Vision
401(k)
FSA/HSA
Life Insurance
Paid Time Off
Wellness Program

Location and Work Details

Austin, TX
Onsite
Travel: 5–10%
Work hours: varies based on department needs
Work setting: office setting
Physical/mental requirements: sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment (telephones, computers)

U.S. Applicant Information

Estimated salary range: $173,000.00 to $276,900.00 USD per year (may include potential sales incentive payments, if applicable)
Salary may vary based on job-related factors including knowledge, skills, experience, and location
May be eligible for bonus and equity

Minimum Education

Bachelor Degree (or Advanced Degree/PhD equivalent)

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2mo ago

Machine Learning Engineer

Neuralink Austin, TX

Austin, TX

2mo ago Closed

$199k - $331k/yr Full time Artificial Intelligence Data Analytics Data Processing

This position is no longer accepting applications (closed Sep 27, 2026).

Job Description

Neuralink is hiring a Machine Learning Engineer to build real-time machine learning and signal processing for brain-computer interfaces in Austin, TX (onsite).

Location: Austin, TX (onsite)
Salary: USD 199,000 - 331,000 per year
Education: Bachelor’s degree in a relevant field

Responsibilities

Develop and iterate on models that decode neural data for BCI use cases
Enable reliable typing for people with paralysis at 35 words per minute and support robotics arm control for activities of daily living
Define research questions that guide development of neural networks and signal processing algorithms aimed at restoring vision for those affected by blindness
Apply foundational knowledge of neural networks and data science to create model capabilities that serve as the basis for BCI machine learning applications
Lead by example through high standards for how systems are built and operated
Contribute to the hardware roadmap by understanding users and identifying product features with the greatest impact on quality of life

Requirements

Experience writing production-level C/C++/Rust and Python
Proven track record designing, building, and shipping real-time ML products
Strong foundation in signal processing, algorithms, and core software engineering principles
Bachelor’s degree in a relevant field or equivalent experience

Technologies

C
C++
Rust
Python

Benefits

Excellent medical, dental, and vision insurance through a PPO plan
Paid holidays
Commuter benefits
Meals provided
Equity in the form of RSUs (Temporary Employees & Interns excluded)
401(k) plan (Interns initially excluded until they work 1,000 hours)
Parental leave (Temporary Employees & Interns excluded)
Flexible time off (Temporary Employees & Interns excluded)

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2mo ago

Machine Learning Engineer II

7-Eleven Irving, TX

Irving, TX

2mo ago Closed

Full time Ai Ml Artificial Intelligence Azure Data Factory

This position is no longer accepting applications (closed Sep 27, 2026).

Job Description

Use machine learning to turn store telemetry into practical, data-driven outcomes. In this onsite role in Irving, TX, you will design, develop, test, and deploy scalable ML solutions using big data and Azure-based platforms. The work focuses on transforming equipment signals and large datasets into actionable insights that support analytics and decision-making across the business.

Responsibilities

Design, develop, test, and deploy machine learning models and data-driven solutions that convert store equipment telemetry into actionable insights.
Build and optimize scalable data pipelines in enterprise environments using Python, PySpark, and Azure technologies.
Process, analyze, and manipulate large structured and unstructured datasets to support analytics and machine learning initiatives.
Collaborate with data engineers, data scientists, product owners, and business stakeholders to translate requirements into technical implementations.
Develop, evaluate, and tune machine learning models using appropriate algorithms and statistical techniques.
Apply MLOps best practices for deployment, monitoring, and model lifecycle management.
Create visualizations, dashboards, and presentation materials to communicate insights and recommendations to both technical and non-technical audiences.
Participate in code reviews, technical design discussions, and continuous improvement efforts.

Requirements

Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
5+ years of experience delivering big data and machine learning solutions in enterprise environments.
Strong programming experience in Python and PySpark.
Hands-on experience with Azure Databricks, Azure Data Factory (ADF), Azure Kubernetes Service (AKS), Git, and Azure DevOps.
Experience building, training, validating, and deploying machine learning models.
Solid understanding of data structures, algorithms, software engineering principles, and distributed computing concepts.
Experience working with large-scale datasets and cloud-native architectures.
Strong analytical, problem-solving, and communication skills.

Technologies

Python, PySpark
Azure, Azure Databricks, Azure Data Factory (ADF), Azure Kubernetes Service (AKS)
Git, Azure DevOps
Power BI, Tableau

Preferred Qualifications

Experience deploying and operationalizing machine learning models in Azure Databricks.
Experience with MLOps frameworks and CI/CD pipelines for machine learning workloads.
Experience with data visualization tools such as Power BI, Tableau, or equivalent platforms.
Experience working with equipment telemetry data or on equipment maintenance projects.
Knowledge of containerization technologies and cloud-native application development.

Machine Learning Expertise

Clustering and segmentation techniques.
Generalized Linear Models (GLM), Linear Regression, Logistic Regression.
Decision Trees and Random Forests.
Gradient boosting techniques including XGBoost.
K-Nearest Neighbors (KNN), Support Vector Machines (SVM).
Artificial Neural Networks (ANN) and deep learning concepts.
Model evaluation, feature engineering, hyperparameter tuning, and performance optimization.

Success Factors

Ability to work effectively in a fast-paced, collaborative environment.
Strong ownership mindset and commitment to delivering high-quality solutions.
Ability to communicate complex technical concepts to diverse stakeholder groups.
Passion for continuous learning and innovation in machine learning and cloud technologies.