United States

Data Jobs in United States

3,208 jobs found

Include remote jobs

1mo ago

Data Scientist

SAIC Chantilly, VA

Chantilly, VA

1mo ago Closed

$160k - $200k/yr Full time Analytics Artificial Intelligence Business Analytics

This position is no longer accepting applications (closed Aug 31, 2026).

Job Description

Data Scientist providing Systems Engineer Technical Advisor (SETA) services for AI/ML-enabled software acquisition on the Landmark AOS program, supporting the NRO Ground Enterprise across the end-to-end lifecycle. This on-site role is based in Chantilly, VA and offers a salary range of USD 160,001 - 200,000 per year. A Master's degree is required.

Summary

The Data Scientist delivers SETA support for AI/ML-enabled software acquisitions on the Landmark AOS program, assisting the NRO Ground Enterprise throughout the full lifecycle from planning to deployment.

Responsibilities

Collect and analyze data to support transparency and explainability of AI/ML systems.
Provide technical and engineering support to the Government customer for managing machine learning analytics programs; apply expertise to develop and scale AI/ML models across multiple phenomenologies.
Deliver software architecture guidance and other technical insight to help plan future systems and architectures, including oversight of development contractors.
Apply systems analysis and design methodology to identify technical debt, establish architectural runway, and evaluate efficiency trade-offs against current and proposed cloud-based software designs.
Create briefings and documentation illustrating features, capabilities and mission use cases for the computer vision tool portfolio; develop technical roadmaps and acquisition strategies with supporting documentation to implement them.
Coordinate technical and programmatic interchanges, identify and resolve issues, and provide engineering and technical guidance to enable innovative automated machine learning analytics.
Collaborate closely with LANDMARK AOS staff, including System Engineers, Acquisition Engineers and Domain Experts, to guide the customer in acquiring modern processing applications.

Requirements

Education and experience: Bachelor's degree with 2+ years of related experience, or Master's degree with 0 years related experience.
Active Top Secret clearance with polygraph.
Strong engineering foundation with knowledge of software architectures and machine learning approaches.
Experience with ontologies, training dataset generation, model evaluation and validation, and responsible AI practices.
Domain knowledge in Agile software development practices (Scrum, SAFe) and cloud computing architectures, with experience monitoring software development progress via Agile metrics, identifying risks, discrepancies, and performance issues.
Demonstrated initiative, creative problem-solving and critical thinking abilities.
Proven capability and success working in team environments.
Strong oral and written communication skills on significant technical matters requiring coordination in a high-tempo environment.
Proficiency with MS Office applications.

Technologies

MS Office

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1mo ago

Senior Applied Data Scientist – Forecasting & Decision Systems

Hawaii Foodservice Alliance Honolulu, HI

Honolulu, HI

1mo ago Closed

$145k - $180k/yr Full time Python Senior Advanced Analytics

This position is no longer accepting applications (closed Aug 31, 2026).

Job Description

The role centres on designing and deploying forecasting, optimization, and AI-enabled decision systems to optimize Hawaii Foodservice Alliance’s logistics operations, with a hybrid work arrangement based in Oahu.

Responsibilities

Lead the end-to-end demand forecasting capability from problem framing to production deployment, monitoring, and ongoing improvement.
Develop store-item-day forecasts that capture seasonality, promotions, intermittent demand, stockouts, product life cycles, and the asymmetric costs of over or under ordering.
Set up credible baselines, backtesting frameworks, business-weighted evaluation metrics, and controlled pilots.
Rapidly prototype analytical applications, model-review tools, and operational workflows using modern AI-assisted development platforms.
Translate model outputs into actionable recommendations for buyers, order writers, merchandisers, and operational leaders.
Build production‑level Python and SQL solutions, including batch pipelines, model services, APIs, monitoring, and decision logs.
Measure whether models produce meaningful business outcomes such as reduced distress, improved shelf availability, better ordering, and more efficient allocation of labor and resources.
Design mechanisms to capture user overrides, operational context, and actual outcomes to enable continuous system improvement.
Partner with Data Engineering and Business Intelligence to leverage and extend governed Snowflake and dbt data products.
Collaborate with Software Engineering to integrate models and decision logic into HFA’s internal applications.
Contribute to analytical datasets, KPI definitions, and dashboards that directly support the decision products you own.
Explore optimization approaches for scheduling, routing, purchasing, replenishment, and task prioritization.
Help develop AI-assisted operational monitoring that detects abnormalities, assembles supporting evidence, explains causes, and recommends next actions with human oversight.
Clearly communicate findings to both technical teams and business leaders, including when evidence does not justify deploying a model.

Requirements

At least five years of experience building applied data science, forecasting, machine learning, or decision-support systems, or an equivalent record of production ownership.
Proven ability to move models from experimentation into live business workflows.
Strong Python and SQL skills.
Practical depth in time-series forecasting with rigorous backtesting and benchmarking against simple baselines.
A scientific mindset grounded in hypothesis testing, measurement, uncertainty, and willingness to revise approaches based on evidence.
Ability to translate ambiguous business problems into measurable objectives, constraints, evaluation criteria, and an implementable product.
Experience delivering working software beyond notebooks, including applications, services, automated pipelines, or internal tools.
Experience using AI-assisted coding tools to accelerate development while maintaining tests, version control, security, and maintainable architecture.
Familiarity with production practices such as Docker, orchestration, CI/CD, model monitoring, drift detection, observability, or experiment tracking.
Ability to work directly with operational users, understand decision processes, and explain technical results in practical terms.
Strong judgment on when to apply advanced modeling versus simpler, more interpretable approaches.
Ability to operate independently while collaborating closely with data, BI, software, and business teams.

Technologies

Python, SQL, Snowflake, dbt, Snowpark, Airflow, MLflow, OR-Tools, Gurobi, CPLEX, Pyomo
React, Streamlit, Dash
Docker

Preferred Experience

Demand forecasting in grocery, retail, consumer packaged goods, food distribution, replenishment, or other inventory-intensive settings
Probabilistic or quantile forecasting, hierarchical forecasting, intermittent demand, cold-start forecasting, or demand censored by stockouts
Inventory optimization, safety stock, service-level modeling, or newsvendor-type decisions
Mathematical optimization including routing, scheduling, constraint programming, simulation, or mixed-integer programming
Experience with OR-Tools, Gurobi, CPLEX, Pyomo or similar optimization frameworks
Exposure to Snowflake, dbt, Airflow, MLflow, Snowpark or similar warehouse-centric platforms
Applied LLM or agentic-system experience with tools, structured data, business rules, and human approval workflows
Computer vision, OCR, or vision-language models
Causal inference, promotion-lift analysis, difference-in-differences, synthetic controls, or experimentation in operational settings
Experience building lightweight front ends or internal apps using React, Streamlit, or Dash
Experience with DSD, logistics, warehouse, merchandising, transportation, or multi-location field operations

What Success Looks Like

Develop a clear understanding of HFA’s ordering processes, constraints, and current forecasting methods
Establish a reproducible backtesting and evaluation framework
Replicate the incumbent baseline and identify key forecast error sources
Deliver an initial model and forecast-review prototype for a focused category or area
Show measurable improvement over the baseline on holdout data
Deploy probabilistic forecasts or order recommendations in a controlled pilot
Implement monitoring, drift detection, model versioning, and user-override logging
Set up a plan to measure distress, shelf availability, service level, and adoption
Assess operational and financial impact of the initial forecast pilot
Extend successful approaches to additional categories or locations
Establish a sustainable model development and monitoring process
Deliver or scope a second decision system such as routing, scheduling, or AI-assisted monitoring

Compensation

Salary Range: $145,000–$180,000 per year
Actual compensation determined by qualifications, production experience, technical depth, and internal equity. This range reflects the base salary for the Oahu-based role at posting time.
Candidates near the upper end typically bring production forecasting or optimization ownership, strong software development capabilities, and a track record of measurable operational impact.

Benefits & Wellness

100% employer-paid medical coverage for team members, with subsidized family coverage
Dental, vision, and preventive care benefits
401(k) retirement plan with up to 4% employer match and immediate vesting
Paid vacation, sick leave, holidays, and floating holidays
Employee Assistance Program with free, confidential counseling
Horizon Day — a paid annual day off to volunteer
Wellness programs including gym membership discounts and health initiatives
Flexible spending account
Life insurance
Paid time off

Why This Role

You will directly own a new applied-science capability and shape systems that influence real orders, inventory, routes, labor, shelves, and customer service across Hawaiʻi.
This is a hands-on role that blends scientific thinking with modern AI enabled development and strong engineering judgment to address meaningful operational problems, rather than notebook-only research or traditional reporting.

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1mo ago

AI Engineer

Thermo Fisher Scientific Charlotte, NC 🇺🇸 Remote

Charlotte, NC

1mo ago Closed

$80k - $100k/yr Full time Artificial Intelligence Big Data Cloud Platform

This position is no longer accepting applications (closed Aug 31, 2026).

Job Description

Thermo Fisher Scientific in North Carolina (remote) seeks an AI Engineer (Scientist II, Data Sciences) to design, build, deploy, and optimize AI models and generative AI solutions that advance CRG Digital priorities, collaborating with data scientists, software engineers, and domain experts to translate business needs into scalable AI products.

Responsibilities

Design, develop, and deploy machine learning and generative AI models aligned with CRG Digital priorities, including predictive analytics, NLP/text solutions, automation, and decision-support capabilities.
Apply statistics, programming, data modeling, simulation, and advanced mathematics to address business challenges.
Evaluate model performance with appropriate validation metrics and techniques, then optimize accordingly.
Build reusable pipelines, APIs, and components to enable scalable AI product delivery.
Preprocess, clean, transform, and integrate structured and unstructured data from clinical and operational sources.
Develop and maintain ETL and data workflows that support ML and generative AI workloads.
Work with relational, document, columnar, graph, and object stores; design schemas for AI and analytics use cases.
Uphold data quality, reproducibility, data lineage, and governance compliance.
Collaborate with software engineering and platform teams to integrate AI models into production systems with monitoring and observability.
Support documentation, traceability, and regulatory readiness, including auditability and GxP considerations.
Contribute to CRG Digital product development lifecycle across discovery, prototyping, testing, deployment, and iteration.
Stay current on emerging AI and ML technologies and evaluate opportunities for CRG Digital roadmaps.
Foster an innovative ecosystem through collaboration with external partners and technology collaborators.
Help advance internal digital and AI upskilling via documentation, best practices, and knowledge sharing.

Requirements

Bachelor’s degree or equivalent; Master’s degree preferred.
Minimum 2 years of experience in machine learning, AI model development, or data science.
Educational equivalency or related experience may be considered in lieu of formal degrees.
Proficiency with SQL, Python, Spark, and common AI/ML libraries and packages.
Hands-on experience with generative AI, large language models, NLP, prompt engineering, and LLMOps best practices.
Strong exploratory data analysis skills, including validating, visualizing, and communicating model behavior.
Experience with cloud architecture, distributed computing, and modern ML platforms.
Familiarity with data governance, security, and regulatory compliance, preferably in regulated or clinical settings.
Ability to juggle multiple priorities in a matrixed environment.
Strong analytical thinking, problem-solving, and communication abilities.
Capable of working independently and collaborating effectively with cross-functional teams.
Must be legally authorized to work in the United States or Mexico without sponsorship.
Must pass a comprehensive background check, including a drug screening.
Excellent communication with diverse groups and clear information exchange.
Ability to work in standard office environments, maintaining typical working hours.
Proficiency with standard office equipment and collaboration tools.
Comfort handling pressure while managing multiple projects; may require travel 0-20% as needed.

Technologies

Python, SQL, Spark
TensorFlow, PyTorch, Keras, scikit-learn
LangChain, LangGraph, OpenAI/LLM SDKs
Pandas, NumPy, Jupyter
Databricks, AWS, Azure, GCP; S3, Azure Blob Storage
Git/GitHub

Benefits

Eligible for a variable annual bonus

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1mo ago

Software AI Engineer

AuraOne Human Data Remote 🇺🇸 Remote

Remote

1mo ago Closed

Contract Ai Assisted Code Review Artificial Intelligence Automated Testing

This position is no longer accepting applications (closed Aug 31, 2026).

Job Description

This remote contract role focuses on evaluating production code, debugging traces, and developer-facing AI outputs for correctness, with reviewers reproducing failures, writing minimal failing tests, and explaining fixes to guide model improvements.

Responsibilities

Reproduce candidate code outputs in a sandboxed environment for Software AI Engineer assignments.
Assess AI engineering solutions for correctness, complexity, idiomatic style, and edge-case handling.
Create minimal failing tests that reveal bugs a model output missed.
Compare paired solutions and rank them with a written rationale aligned to the rubric.
Annotate failure modes (compile error, runtime crash, off-by-one, security issue) with severity scores.
Document recurring code-generation failures to guide the modeling team’s focus.
Calibrate against gold-standard reviews to maintain inter-rater agreement above target.

Requirements

Strong day-to-day engineering experience you can read, run, and debug unfamiliar code for Software AI Engineer work.
Comfort writing concise unit tests that capture a single failure mode.
Familiarity with at least one of: pytest, Jest, JUnit, Go test, RSpec, or equivalent.
Clear written reasoning that can persuade another senior engineer.
Reliable async availability for at least 10 hours per week.

Technologies

pytest
Jest
JUnit
Go test
RSpec

Why this role matters

Engineering model quality depends on code that compiles, passes tests, and handles edge cases. AuraOne pairs experienced engineers with the modeling team to evaluate outputs the way a code reviewer would.

Example tasks

Reproduce a generated engineering solution to a coding task, run the test suite, and grade it.
Write the smallest failing test that demonstrates a model's edge-case bug.
Compare two paired solutions and rank them with a rubric-based rationale.
Triage a security issue surfaced by a model and document the expected patch.

NICE TO HAVE

Open-source contributions or a public portfolio showing production-quality code.
Experience with the target language's standard tooling, linters, and idiomatic style guides.
Familiarity with security-review checklists (OWASP, CWE) and AppSec patterns.

Skills

Code review
Debugging
Unit testing
Software engineering judgment
AI engineering
Software engineering
AI model evaluation

Work model

Remote — US-eligible. Independent specialist contractor. Employment type: CONTRACTOR. Applicants must be authorized to work from US.

Compensation

Hourly rate confirmed after the interview process.

Application process

Apply through AuraOne's specialist intake for role-specific routing and review. Final project scope, schedule, and contractor terms are confirmed before placement.

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1mo ago

AI Engineer

AuraOne Human Data Remote 🇺🇸 Remote

Remote

1mo ago Closed

$50 - $120/hr Contract Artificial Intelligence Automated Testing Data & Ai

This position is no longer accepting applications (closed Aug 31, 2026).

Job Description

Remote AI Engineer role focused on evaluating production code and AI outputs for correctness by reproducing failures, writing the unit tests the model should have written, and explaining fixes to guide the modeling team.

Job details

Location: Remote
Salary: USD 50 - 120 per hourly
Type: Contract

Responsibilities

Execute candidate code outputs in a sandbox to verify AI Engineer assignments and reproduce issues.
Assess AI engineering submissions for correctness, complexity, idiomatic style, and edge-case handling.
Write minimal failing tests that expose bugs a model output missed.
Compare paired solutions and assign a ranking with a written rationale aligned to the rubric.
Identify and label failure modes (compile error, runtime crash, off-by-one, security issue) with severity scores.
Document recurring code-generation failures so the modeling team can target them.
Calibrate against gold-standard reviews to maintain inter-rater agreement above target.

Requirements

Strong day-to-day engineering experience — you can read, run, and debug unfamiliar code for AI engineer work.
Ability to craft concise unit tests that isolate a single failure mode.
Familiarity with at least one of: pytest, Jest, JUnit, Go test, RSpec, or equivalent.
Clear written reasoning — your review notes should persuade a senior engineer.
Reliable async availability for at least 10 hours per week.
Prior code-review or technical-interview-grading experience is a plus.

Technologies

pytest
Jest
JUnit
Go test
RSpec
C#
C++
GoLang
JAVA
.NET
PHP
Python

Example Tasks

Reproduce a generated engineering solution for a coding task, run the test suite, and evaluate it.
Draft the smallest failing test that demonstrates a model's edge-case bug.
Compare two paired solutions and rank them with a rubric-based written justification.
Triage a security issue surfaced by a model and document the patch the model should have produced.

Nice to Have

Open-source contributions or a public portfolio showing production-quality code.
Experience with the target language's standard tooling, linters, and idiomatic style guidelines.
Familiarity with security-review checklists (OWASP, CWE) and AppSec patterns.

Skills

Code review
Debugging
Unit testing
Software engineering judgment
AI engineering
C#
C++
GoLang
JAVA
.NET
PHP
Python

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1mo ago

Data Engineer (Backend Python Development)

Green Courte Residential Holdings LLC Clearwater, FL

Clearwater, FL

1mo ago Closed

$90k - $115k/yr Full time Python Apache Airflow Azure

This position is no longer accepting applications (closed Aug 31, 2026).

Job Description

Green Courte Residential Holdings LLC is expanding its data capabilities with a Data Engineer I based onsite in Clearwater, Florida. This role supports the data and analytics ecosystem across GCRH and its managed companies, acting as a technical visionary to identify new efficiencies through technology while delivering reliable data pipelines and analytics to inform operations. The position emphasizes hands-on backend Python development alongside building scalable data solutions and fostering data-driven decisions.

Responsibilities

Identify, design, implement, and manage scalable and reliable data pipelines and monitoring systems.
Develop a deep understanding of Green Courte and its platform investments' data to rapidly create new data assets or augment existing assets to provide insights into key operational areas.
Identify opportunities for operational efficiency through automation and system integration.
Uphold data integrity and establish scalable quality checks and controls.
Maintain clear data documentation to enable data accessibility for users with varying technical skills; monitor usage to maximize impact.
Manage Green Courte’s data catalog and ensure robust data discoverability for all end users.
Provide ad hoc analytical support to inform strategic decision-making.
Perform other duties as assigned.

Requirements

Bachelor’s or Master’s degree in Computer Science, Information Systems, Mathematics or a related STEM field.
Advanced proficiency in Python and SQL with strong software engineering fundamentals.
Experience building Python-based API services using Flask or FastAPI, data processing with Pandas or Polars, and Pydantic-based data validation.
Experience orchestrating complex data pipelines with Airflow.
Experience developing event-driven data pipelines using RabbitMQ or SQS.
Experience sourcing data from third-party APIs and building production-ready data models using dbt or SQLMesh.
Experience with modern cloud data platforms such as AWS, Azure, GCP, and Snowflake.
Experience using Git for version control and managing CI/CD pipelines with GitHub.
Experience working in Linux environments, including shell scripting and operational troubleshooting.
Experience with observability and structured logging, using Grafana or similar tools.
Full-stack mindset with willingness to develop across layers to ship data products.
Excellent communication skills; able to explain technical solutions to non-technical audiences.
Highly organized and detail-oriented; able to work efficiently under pressure in a fast-paced environment.
Ability to work independently with limited supervision.
Curious, lifelong learner with the ability to distinguish between trends and enduring practices in data technology.
Collaborative team player.

Technologies

Python
SQL
Flask
FastAPI
Pandas
Polars
Pydantic
Airflow
RabbitMQ
SQS
dbt
SQLMesh
AWS
Azure
GCP
Snowflake
Git
GitHub
Linux
Grafana
Docker
Kubernetes
Terraform

Benefits

Medical/Dental/Vision Insurance
Health Savings Account (HSA)
Flexible Spending Account (FSA)
Paid Parental Leave
Short-term Disability
Long-term Disability
Industry-leading PTO
Paid Holidays
401k program (including match)
Tuition reimbursement
Paid training
Bonus/Incentive Program
Employee Assistance Program (EAP)

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1mo ago

Data Scientist/Analytics Engineer

Trideum Corporation Killeen, TX

Killeen, TX

1mo ago Closed

Full time Analytics Army Vantage Artificial Intelligence

This position is no longer accepting applications (closed Aug 31, 2026).

Job Description

This on-site Analytics Engineer role in Killeen, TX will establish data-driven decision-making and support operational evaluations for the US Army Operational Evaluation Command.

Responsibilities

Develop and sustain decision-support tools across executive to engineering levels, including dashboards and AI pipelines.
Create data pipelines and visualizations within enterprise platforms such as Army Vantage to enable real-time oversight of operational tests and evaluations.
Maintain strict data traceability from source data and underlying assumptions through analyses to final evaluation.
Collaborate with customers and mission partners to gather requirements and shape effective solutions.
Identify data sources, design data pipelines, and implement storage solutions aligned with customer needs.
Communicate technical findings and recommendations to both technical and non-technical stakeholders, including senior leadership.
Travel may be required, up to 25% of the time.

Requirements

Bachelor’s degree from an accredited institution in a technical discipline (data science, engineering, mathematics, science, or computer science).
Five or more years of related professional experience.
Active DoD Secret Clearance or U.S. citizenship with the ability to obtain/maintain a DoD Secret Clearance is required.
Strong background in data science, analytics, and/or data engineering with solid knowledge of statistics and mathematics.
Proficiency in data analysis and visualization using Python, R, and SQL.
Experience with data visualization tools such as Tableau, Power BI, or Qlik.
Experience with data management platforms like ADVANA, Palantir Foundry, Databricks, Snowflake, and Azure Synapse Analytics.
Proven ability to independently solve technical and operational problems within a collaborative team environment.
Excellent written and verbal communication skills.
Familiarity with DoD systems and processes.