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1mo ago

Senior Data Engineer

NIRA Inc. Washington, DC

Washington, DC

1mo ago Closed

$170k+/yr Full time Senior Apache Airflow Aws Govcloud

This position is no longer accepting applications (closed Sep 8, 2026).

Job Description

NIRA Inc. is seeking a Senior Data Engineer to support the U.S. Department of Justice Digital Evidence Review Platform program. In this onsite role in Washington, DC, you will help design and run high-volume ingestion and processing pipelines that protect integrity and provenance while keeping auditability, access control, and chain-of-custody information intact.

You will be responsible for end-to-end pipeline engineering across development, testing, deployment, and operations, with an emphasis on resilient processing for structured and unstructured data used in digital evidence workflows.

Responsibilities

Design, develop, test, operate, and optimize high-volume data ingestion, transformation, integration, and processing pipelines.
Ingest, normalize, enrich, validate, store, search, export, archive, and restore structured and unstructured data.
Process inputs including forensic extraction packages, documents, messages, multimedia, call records, geolocation data, cloud-provider returns, metadata, and outputs from Government-furnished parsers and external systems.
Implement validation, hashing, error handling, retry, reconciliation, reprocessing, and data-quality controls.
Preserve source identifiers, processing history, lineage, provenance, and chain-of-custody events.
Support OCR, transcription, translation, deduplication, metadata extraction, entity extraction, and enrichment workflows.
Develop schemas, canonical data models, metadata structures, and open, portable export formats.
Support search, analytics, and AI/ML-enabled processing while maintaining human oversight and auditability.
Automate deployment and testing through CI/CD and configuration-management practices.
Tune pipeline performance and troubleshoot failures across development, test, UAT, production, and disaster-recovery environments.
Maintain technical documentation and collaborate with architects, software engineers, cloud integrators, cybersecurity personnel, and product specialists.

Requirements

Bachelor's degree in engineering, mathematics, or science.
At least 15 years of relevant experience in data engineering, data integration, data architecture, software engineering, or large-scale data-processing.
A master's degree may substitute for two years of required experience; a PhD may substitute for four years.
Extensive experience designing, developing, and maintaining enterprise data ingestion, transformation, integration, and processing pipelines.
Experience processing structured and unstructured data from multiple sources and formats.
Experience with data modeling, metadata, schema design, data lineage, data quality, error handling, reconciliation, and audit logging.
Experience developing in Python, Java, Scala, SQL, or comparable data-engineering languages.
Experience with cloud-based data platforms, distributed processing, object storage, databases, search platforms, or analytics environments.
Experience supporting CI/CD, automated testing, configuration management, performance tuning, and production troubleshooting.
S. citizenship and ability to meet DOJ residency and personnel-security requirements.
Ability to obtain and maintain a High-Risk Public Trust investigation and PIV credential.

Technologies

Python, Java, Scala, SQL
CI/CD, OCR
Spark, Databricks, Kafka, Airflow
AWS GovCloud, Azure Government
FedRAMP-authorized SaaS
LLM/RAG

Preferred Qualifications

Experience with digital evidence, forensic data, eDiscovery, law-enforcement data, case-management data, or other high-integrity federal datasets.
Experience with AWS GovCloud, Azure Government, FedRAMP-authorized SaaS, or hybrid federal cloud environments.
Experience processing PDFs, text, messages, multimedia, call records, geolocation data, forensic extraction files, or large document collections.
Experience with OCR, natural-language processing, entity extraction, transcription, translation, deduplication, AI/ML enrichment, or LLM/RAG pipelines.
Experience with Python-based data frameworks, Spark, Databricks, Kafka, Airflow, cloud-native data services, or comparable technologies.
Experience implementing hashing, immutable audit records, provenance, lineage, retention, archival, and data-restoration controls.
Experience designing open-format exports, APIs, canonical schemas, or data-exchange interfaces that reduce vendor lock-in.

Location: Washington, DC (onsite). Compensation: USD 170,000 per yearly.

Education: Bachelor's degree in engineering, mathematics, or science.

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1mo ago

Data Scientist

BOOZ, ALLEN & HAMILTON, INC. Fort Meade, MD

Fort Meade, MD

1mo ago Closed

$99k - $225k/yr Full time Amazon Emr Analytics Artificial Intelligence

This position is no longer accepting applications (closed Sep 7, 2026).

Job Description

Booz Allen Hamilton, Inc. is seeking a Data Scientist to support mission-focused work in Fort Meade, MD. In this onsite role, you will apply statistical methods, machine learning, data mining, and predictive analytics to turn complex structured and unstructured data into objective, actionable insights.

What you’ll do

Contribute to advanced analytic initiatives on mission-focused projects.
Use statistical methods, machine learning, data mining, and predictive analytics to extract value from diverse data sources and address operational challenges.
Partner with clients to understand questions and needs.
Explore data-rich environments to identify and assemble the information needed to answer client problems.
Lead teammate efforts and support development of algorithms and systems.
Select appropriate tools and frameworks to transform disparate data points into objective answers clients can use for informed decisions.
Provide a deep understanding of the data, its meaning, and how it can be applied.
Apply leadership and data science expertise to create real-world impact.
Work as part of a team applying data science for good.

Qualifications

3+ years of experience with data exploration, data cleaning, data analysis, data visualization, or data mining.
3+ years of experience with statistical and general-purpose programming languages for data analysis.
3+ years of experience analyzing structured and unstructured data sources.
Experience developing predictive data models, quantitative analyses, and visualization of targeted data sources.
Experience with natural language processing, text mining, or machine learning techniques.
Knowledge of ETL tools such as DBT and Airflow.
Secret clearance.
HS diploma or GED.

Tools and technologies

Machine learning, artificial intelligence, statistical methods, data mining, predictive analytics
Natural language processing, text mining
ETL tools: DBT, Airflow
Spark, Databricks, Hadoop, Hive, AWS EMR, Kafka
Tableau, Qlik, Power BI, ArcGIS

Pay and location

Location: Fort Meade, MD (onsite)
Compensation: USD 99,000 - 225,000 per year

Clearance and security

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.
Secret clearance is required.

Identity verification and interview rules

During the hiring process, you will be asked to complete an identity verification process that uses advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud.
You are expected to be on camera during interviews and assessments.
Booz Allen reserves the right to take your picture to verify your identity and prevent fraud.
Use of artificial intelligence or other tools to assist with interview responses (in-person or virtual) is prohibited unless permission is explicitly provided.

Benefits

Health, life, disability, and financial benefits
Retirement benefits
Paid leave
Professional development
Tuition assistance
Work-life programs
Dependent care
Recognition awards program acknowledging employees for exceptional performance and superior demonstration of company values
Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in benefit programs
Individuals that do not meet the threshold are eligible for select offerings, not inclusive of health benefits

Work model

Onsite: Work will primarily be performed at a Booz Allen office or customer facility, with collaboration required with colleagues and customers as needed.

Non-discrimination

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran, or any other status protected by applicable federal, state, local, or international law.

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1mo ago

Staff, Data Scientist

Walmart Sunnyvale, CA

Sunnyvale, CA

1mo ago Closed

$143k - $286k/yr Full time Big Data Bigquery Cloud Platform

This position is no longer accepting applications (closed Sep 7, 2026).

Job Description

Walmart is hiring a Staff Data Scientist in Sunnyvale, CA (onsite) to turn complex data into actionable business insights. In this role, you will build and deploy production-ready predictive machine learning solutions focused on fraud and risk detection, working closely with cross-functional partners.

Role Summary

As a Staff Data Scientist, you will use advanced analytics and machine learning to transform large-scale datasets into practical recommendations. The position includes hands-on development of predictive models, evaluation of model performance, and collaboration on scalable, production-ready data science solutions for fraud and risk detection.

Responsibilities

Perform hands-on data exploration, processing, and analysis on large-scale datasets.
Apply machine learning, deep learning, and data mining techniques to develop robust predictive models for eCommerce fraud detection, financial services fraud detection, anomaly detection, and abusive returns.
Extract and analyze data from data warehouses and cloud platforms, including feature engineering, back-test modeling, and performance evaluation.
Present findings and recommendations to stakeholders.
Research, develop, and implement state-of-the-art algorithms addressing complex business challenges.
Partner with cross-functional teams to deploy scalable, production-ready data science solutions.

Requirements

Strong expertise in data mining, machine learning, statistical analysis, and deep learning.
Proficiency in Python and experience with open-source machine learning and data science frameworks.
Experience working with large datasets using distributed computing platforms such as BigQuery, Hive, or Spark.
Experience in cloud environments, including Google Cloud Platform (GCP) or Microsoft Azure.
Familiarity with AI agents and practical AI-driven applications.
Strong database and querying skills, including BigQuery, Hive, and SQL.
Programming experience in Python, Java, or JavaScript.
Advanced degree in a STEM field (Master's or PhD preferred) and at least five years of relevant industry experience.
Ability to thrive in a fast-paced environment and communicate effectively with both technical and non-technical stakeholders.

Technologies

Python
BigQuery
Hive
Spark
SQL
Google Cloud Platform (GCP)
Microsoft Azure
Java
JavaScript
scikit learn
tensorflow
torch

About the Team

Fraud and Risk Detection Data Science team at Walmart Global Tech.
Cross-functional team across data science, big data, IT infrastructure, and business operations.
Develop scalable predictive models and analytics solutions using advanced machine learning, deep learning, and optimization techniques.
Work with large volumes of business and customer data generated across Walmart’s online and offline commerce platforms.

Minimum Qualifications

Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years of experience in an analytics related field.
Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years of experience in an analytics related field.
Option 3: 6 years of experience in an analytics or related field.

Preferred Qualifications

Data science, machine learning, optimization models, and a PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, or Econometrics.
Successful completion of one or more assessments in Python, Spark, Scala, or R.
Using open source frameworks such as scikit learn, tensorflow, or torch.
Background in creating inclusive digital experiences, including knowledge of implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility.
Knowledge of accessibility best practices and experience aligning with Walmart accessibility standards and guidelines supporting an inclusive culture.

Location and Work Details

Location: Sunnyvale, CA (onsite)
Primary location address: 815 Eleventh Ave, Sunnyvale, CA 94089-4731, United States of America
Minimum experience: 2 years

Compensation

Salary range: USD 143,000 - 286,000 per year

Benefits

Health benefits including medical, vision and dental coverage.
401(k).
Stock purchase.
Company-paid life insurance.
PTO including sick leave, parental leave, family care leave, bereavement, jury duty, and voting.
Short-term and long-term disability.
Company discounts.
Military Leave Pay.
Adoption and surrogacy expense reimbursement.
Live Better U (Walmart-paid education benefit program).
Annual or quarterly performance bonuses.
Additional compensation for certain positions may include stock.
PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes.

Drug-Free Workplace

Walmart and its subsidiaries are committed to maintaining a drug-free workplace and have a no tolerance policy regarding the use of illegal drugs and alcohol on the job.

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1mo ago

Data Scientist, Research, Search Platforms

Google Mountain View, CA

Mountain View, CA

1mo ago Closed

$174k - $253k/yr Full time Big Data Data Data Analysis

This position is no longer accepting applications (closed Sep 7, 2026).

Job Description

The Search Platform Data Science team at Google focuses on understanding, measuring, and improving Google Search systems, with an emphasis on the end-to-end user experience. In this role, you will work at the intersection of Advanced Causal Inference, Product Analytics, and Machine Learning, helping teams make measurement and decision-making stronger across complex, real-world environments.

You will be responsible for methodological innovation and analytics execution, from defining how to measure user experience to building scalable pipelines and translating results into recommendations. The work spans topics including Experimentation, Reliability, Velocity, Latency, Capacity, Content, Regulation, and Antiscraper.

Role focus

Understand and improve Search systems by combining measurement approaches with analytical rigor across the user journey.
Pioneer methodological innovations to capture and improve end-to-end user experience, including scaling User-Perceived Reliability metrics.
Apply advanced causal inference techniques to measure the impact of user friction on long-term retention.
Prototype and apply creative workarounds when clean data is unavailable, including using LLMs to synthesize ground-truth labels.
Drive analytical excellence across the organization by authoring frameworks and best practices to educate the broader Data Science community.

Responsibilities

Extract strategic insights from large, complex datasets that include client-side and server-side logs, tackling intricate, non-routine analytical problems to optimize the user experience for AIM and AIO products.
Lead end-to-end analyses, including data ingestion, requirements specification, processing, modeling, ongoing deliverables, and professional presentations.
Build and iteratively refine analysis pipelines to provide insights at scale.
Collaborate cross-functionally with engineers and multiple teams (including Platform and Product) to identify opportunities, design improvements, and assess impact for AI products.
Develop strategic business recommendations, such as growth headroom estimates, cost-benefit assessments of engineering optimizations, and marketing campaign effectiveness, and present findings to multiple leadership levels.

Requirements

Master’s degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
Minimum experience: 5 years using analytics to solve product or business problems, including coding (Python, R, SQL) and querying databases or conducting statistical analysis; alternatively, 3 years with a PhD.
Ability to take open-ended problems, define them more precisely over time, and work toward solutions.

Preferred qualifications

8 years using analytics to solve product or business problems, including coding (Python, R, SQL) and querying databases or conducting statistical analysis; alternatively, 6 years with a PhD.

Technologies

Python
R
SQL
LLMs

Location and compensation

Location: Mountain View, CA (onsite)
Salary: USD 174,000 - 253,000 per year
Bonus target: 15%
Additional compensation: equity
Benefits: benefits

Work location preference

Applicants can share a preferred working location from: Mountain View, CA, USA; Cambridge, MA, USA

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1mo ago

Data Scientist, Analytics (Technical Leadership)

Meta Fremont, CA

Fremont, CA

1mo ago Closed

$210k - $281k/yr Full time Manager Analytics Artificial Intelligence

This position is no longer accepting applications (closed Sep 7, 2026).

Job Description

Meta is seeking an experienced Data Scientist, Analytics (Technical Leadership) to drive measurable impact across product areas. In this onsite role in Fremont, CA, you will use complex data analysis to shape product development, establish and track success, and clearly communicate insights to stakeholders while providing technical leadership.

What you’ll do

Use analytical and statistical methods to tackle challenging problems with complex data sets
Apply expertise in quantitative analysis, experimentation, and data mining to inform product strategy
Define and measure success through goal setting, forecasting, and monitoring key metrics
Collaborate with cross-functional partners to inform and execute product strategy and investment decisions
Develop a long-term vision and strategy for programs and products
Partner with executives to define and develop data platforms and instrumentation
Communicate insights and recommendations to stakeholders in an effective, actionable way
Set team goals by defining success metrics and forecasting changes
Support roadmap development and coordinate analytics efforts across teams

Minimum qualifications

Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
5+ years of experience with data querying languages (for example, SQL), scripting languages (for example, Python), and/or statistical or mathematical software (for example, R, SAS, Matlab)
8+ years of experience leading analytics work in an IC capacity, working collaboratively with Engineering and cross-functional partners to guide data-influenced product planning, prioritization, and strategy development
Experience leading complex analytics projects across multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics, and Finance
Experience with predictive modeling, machine learning, and experimentation or causal inference methods
Ability to communicate complex technical concepts clearly, precisely, and with actionable detail

Technologies

SQL, Python, R, SAS, Matlab
Machine learning

Preferred qualifications

10+ years of experience communicating analysis results to leadership teams to influence strategy
Master’s or Ph.D. degree in a quantitative field
10+ years of experience performing complex quantitative analysis in product analytics
Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact (for example, efficiency gains or quality improvements)
Experience adhering to and implementing responsible, ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews
Demonstrated ongoing AI skill development, such as prompt/context engineering and agent orchestration, and staying current with emerging AI technologies

Location: Fremont, CA (onsite)
Compensation: USD 210,000 - 281,000 per year
Experience: 8+ years

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1mo ago

Lead Data Scientist

Onos Health San Francisco, CA

San Francisco, CA

1mo ago Closed

$200k - $225k/yr Full time Manager Analytics Claims Analytics

This position is no longer accepting applications (closed Sep 7, 2026).

Job Description

Onos Health is hiring a Lead Data Scientist (hybrid) in San Francisco to take ownership of core analytics and AI model development for payers. The role is both strategic and hands-on, with a focus on measuring clinical appropriateness and identifying cost savings across behavioral health.

Responsibilities

Design and deploy predictive, risk-scoring, and optimization models to identify waste, inappropriate utilization, and care improvement opportunities across behavioral health services.
Contribute to the evolution of the data science stack, including feature stores and pipelines, as well as model monitoring and evaluation frameworks.
Analyze claims and clinical data to uncover trends, outliers, and actionable insights.
Partner with client-facing teams to translate complex models into clear insights that support ROI, payer workflows, and impactful dashboards.
Work closely with the CEO, CPO, and engineering team to shape product direction, data strategy, and key client engagements.

Requirements

8+ years of experience in data science or advanced analytics (healthcare or health plans preferred), with claims and clinical data experience strongly preferred.
Strong expertise in statistical modeling, causal inference, and machine learning.
Working proficiency with Python and SQL, plus related libraries such as scikit-learn, statsmodels, and PyTorch or similar tools.
Familiarity with healthcare data standards, including claims, eligibility, and EHR or clinical data, and coding sets such as ICD, CPT, and HCPCS.
Experience building production-grade models and deploying them in analytical or product environments.
Proven ability to build, mentor, and lead data science or analytics teams.
An entrepreneurial approach: resourceful, proactive, comfortable with ambiguity, and able to move quickly.
Strong communication skills, including the ability to translate complex analyses into business-relevant insights.
Exceptional references from colleagues and former managers.

Technologies

Python, SQL, scikit-learn, statsmodels, PyTorch, ICD, CPT, HCPCS

Location and Employment Details

Location: San Francisco, CA (hybrid)
Salary range: USD 200,000 - 225,000 per year
Minimum experience: 8 years

Benefits

Flexible hybrid schedule: approximately 3 days per week in the San Francisco office (Financial District)
Unlimited vacation policy
Paid parental leave
Medical, dental, and vision insurance
Pre-tax commuter benefits
401(k)
Significant equity as an early employee
Direct mentorship from experienced founders
Ground-floor opportunity to help build a team and culture
Regular team events and off-sites
Company-provided equipment and home office setup

Why Onos Health

Meaningful impact: help address fundamental problems in healthcare
Direct collaboration: work alongside experienced founders with deep healthcare and data expertise
Culture: join a high-performing, transparent, results-oriented team
Ownership: significant responsibility and autonomy from day one
Opportunity: play a pivotal role in building a fast-growing, category-defining healthcare AI company

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1mo ago

Senior Data Scientist - AI Trainer

DataAnnotation Round Lake, IL 🇺🇸 Remote

Round Lake, IL

1mo ago Closed

$50 - $100/hr Contract Senior Ai Trainer Artificial Intelligence

This position is no longer accepting applications (closed Sep 7, 2026).

Job Description

DataAnnotation is seeking a Senior Data Scientist - AI Trainer to support the training of AI models focused on quantitative reasoning. In this fully remote contract role, you will review AI-generated quantitative work, build and solve training problems, and provide feedback that helps systems improve how they analyze data and scientific scenarios.

The position is based in Illinois (remote) and is paid on an hourly basis. Work is available for qualified candidates in the US, Canada, UK, Ireland, Australia, and New Zealand.

Key Responsibilities

Review AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, checking for both technical accuracy and real-world validity.
Create and solve quantitative problems used for training and benchmarking AI systems across areas such as forecasting, experimental analysis, optimization, and statistical inference.
Produce clear technical explanations and maintain well-documented analytical code.
Deliver feedback that directly influences the next generation of AI models built for quantitative reasoning.

Required Qualifications

3+ years of hands-on experience in a quantitative role or research environment, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or a related field.
Coding experience is required, including the ability to write and review analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experiment design, including examples such as A/B testing, hypothesis testing, regression, classification, and time-series forecasting.
Fluency in English (native or bilingual level) with strong writing skills.
A bachelor’s degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar). A Master’s or PhD is a plus.
Relevant credentials are a plus, such as Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise.

Compensation and Employment Details

Job type: contract
Location: Illinois (remote)
Pay: USD 50 to 100 per hour
Some projects may include bonus rates.

Assessment and Onboarding

After you sign up for an account, you will take a short assessment (serving as the company’s interview process). If you pass, you will receive an email confirmation and paid work will become available on the platform.

Additional Notes

Payment is made via PayPal.
The company will never ask applicants for money.
This role is only available to candidates in the US, Canada, UK, Ireland, Australia, and New Zealand.

Benefits

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
Flexible schedule: choose which projects you take on and when you work, using your own computer from home.
Competitive pay: projects are paid hourly at USD 50 to 100 per hour, with bonus rates available on some projects.
Impact: help shape AI systems designed to reason about data and analytics.