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Data Reviewer Jobs in Oregon (NOW HIRING)

Data annotation and quality review * Exploratory data analysis and model fail state analysis * Contribute to model governance, documentation, and explainability frameworks aligned with internal and ...

... data for review by managers and other stakeholders. * Identify and analyze industry trends with business strategy implications. * Maintain library of model documents, templates, or other reusable ...

OR

$80K - $180K/yr

Data-driven decision making is an increasingly important part of our company culture, and our Data ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Lead Data Engineer

Beaverton, OR · On-site

$119K - $143K/yr

LEAD, DATA ENGINEER - NIKE [Beaverton, OR - USA] WHO YOU'LL WORK WITH Consumer Product and ... Participate in code reviews and contribute to a culture of collaboration, innovation, and ...

Comfortable navigating multiple digital platforms, EMRs, and data systems. * Must have strong ... Ability to review and analyze large volumes of medical and billing data. * Strong focus and ...

Develop and maintain data semantic layers and knowledge graphs for enterprise-scale data ... Employees should review all role requirements and apply only for positions for which they are ...

OR

$67.25 - $90/hr

Lead architecture reviews, solution design sessions, and technical governance across enterprise initiatives. * Design metadata-driven frameworks, reusable architecture patterns, and standardized data ...

The contractor shall conduct quarterly reviews to track cost efficiency, assess system performance ... Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) ...

Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry. * Provide feedback and domain-specific insights to improve AI models in computational ...

... reviews with data-driven recommendations - Travel to sites as needed to support data validation, stakeholder engagement, and project alignment Qualifications Required: - Bachelor's degree in Data ...

The contractor shall conduct quarterly reviews to track cost efficiency, assess system performance ... Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) ...

Senior Data Architect

Odell, OR

$69 - $92.25/hr

D&A - Data & Analytics Work Shift: Day Work Days: MON-FRI Scheduled Hours: 9 AM-5:30 PM Scheduled ... Lead architecture reviews and ensure alignment with enterprise IT strategy. Drive cross-functional ...

Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry. * Provide feedback and domain-specific insights to improve AI models in computational ...

Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry. * Provide feedback and domain-specific insights to improve AI models in computational ...

OR · On-site

... reviews with data-driven recommendations - Travel to sites as needed to support data validation, stakeholder engagement, and project alignment Qualifications Required: - Bachelor's degree in Data ...

Showing results 41-60

Data Reviewer information

See Oregon salary details

$13

$27

$45

How much do data reviewer jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for data reviewer in Oregon is $27.75, according to ZipRecruiter salary data. Most workers in this role earn between $15.24 and $38.37 per hour, depending on experience, location, and employer.

What is the difference between Data Reviewer vs Data Analyst?

AspectData ReviewerData Analyst
Required CredentialsTypically a bachelor's degree in data management, IT, or related fields; certifications like CDMP are commonBachelor's degree in statistics, data science, or related fields; certifications like CAP or Microsoft certifications are common
Work EnvironmentMostly office-based, working with data validation tools and softwareOffice or remote, analyzing data sets, creating reports, and visualizations
Employer & Industry UsageUsed in industries like finance, healthcare, and government for data quality assuranceUsed across industries for data-driven decision making and reporting

While both roles involve working with data, Data Reviewers focus on validating and ensuring data accuracy, whereas Data Analysts interpret data to generate insights. Understanding these differences helps in choosing the right career path or job search focus.

What is a data reviewer?

A data reviewer helps an organization review and interpret data for accuracy and interpretation. Data reviewers are necessary for many fields, including software development, quality assurance, medical and health care professions, and accounting, to name a few. Your responsibilities and duties are to look through collected data that has been entered into a spreadsheet or other database. You check it for any errors and manage issues you find. Some data reviewer positions, such as in medical research, include an analytical component; you help the research team to glean insight from the collected data.

What are the key skills and qualifications needed to thrive as a data reviewer, and why are they important?

To thrive as a Data Reviewer, you need strong analytical skills, attention to detail, and typically a background in life sciences, statistics, or a related field. Familiarity with data management systems, electronic data capture (EDC) platforms, and compliance standards such as GCP is commonly required. Excellent problem-solving, critical thinking, and communication skills help you identify discrepancies and collaborate with cross-functional teams. These competencies are crucial for ensuring data integrity, regulatory compliance, and the reliability of research outcomes.

How does a data reviewer typically collaborate with other teams to ensure data quality?

Data Reviewers work closely with data entry specialists, analysts, and project managers to verify the accuracy and consistency of datasets. They often participate in cross-functional meetings to discuss data discrepancies and establish best practices for data validation. This collaboration helps maintain high-quality data standards and ensures that any issues are promptly identified and resolved, supporting the overall goals of the organization.
What job categories do people searching Data Reviewer jobs in Oregon look for? The top searched job categories for Data Reviewer jobs in Oregon are:
What cities in Oregon are hiring for Data Reviewer jobs? Cities in Oregon with the most Data Reviewer job openings:
What are popular job titles related to Data Reviewer jobs in OR? For Data Reviewer jobs in OR, the most frequently searched job titles are:
Infographic showing various Data Reviewer job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $57,710 per year, or $27.7 per hour.

Full-time

Re-posted 25 days ago


Job description

Who are we?

Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines.  Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.

Summary
 
As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh, you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM) solutions that power next-generation compliance and surveillance systems. You'll work on highly specialized problems at the intersection of natural language processing, communications intelligence, financial supervision, and regulatory compliance, where unstructured data from emails, chats, voice transcripts, and trade communications hold the keys to uncovering misconduct and risk.
 
The role will involve working with other Senior Data Scientists and mentoring Associate Data Scientists in analyzing complex data, generating insights, and creating solutions as needed across a variety of tools and platforms. This role demands both technical excellence in NLP modeling and a deep understanding of financial domain behavior-including insider trading, market manipulation, off-channel communications, MNPI, bribery, and other supervisory risk areas. The ideal candidate for this position will possess the ability to perform both independent and team-based research and generate insights from large data sets with a hands-on/can do attitude of servicing/managing day to day data requests and analysis.
 
This role also offers a unique opportunity to get exposure to many problems and solutions associated with taking machine learning and analytics research to production. On any given day, you will have the opportunity to interface with business leaders, machine learning researchers, data engineers, platform engineers, data scientists and many more, enabling you to level up in true end-to-end data science proficiency.
How will you contribute?
  • Collect, analyze, and interpret small/large datasets to uncover meaningful insights to support the development of statistical methods / machine learning algorithms.
  • Lead the design, training, and deployment of NLP and transformer-based models for financial surveillance and supervisory use cases (e.g., misconduct detection, market abuse, trade manipulation, insider communication).
  • Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunities
  • Data annotation and quality review 
  • Exploratory data analysis and model fail state analysis 
  • Contribute to model governance, documentation, and explainability frameworks aligned with internal and regulatory AI standards.
  • Client/prospect guidance in machine learning model and analytic fine-tuning/development processes
  • Provide guidance to junior team members on model development and EDA
  • Work with Product Manager(s) to intake project/product requirements and translate these to technical tasks within the team's tooling, technique and procedures
  • Continued self-led personal development
What will you bring?
  • Strong understanding of financial markets, compliance, surveillance, supervision, or regulatory technology
  • Experience with one or more data science and machine/deep learning frameworks and tooling, including scikit-learn, H2O, keras, pytorch, tensorflow, pandas, numpy, carot, tidyverse
  • Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc...)
  • Strong knowledge of key programming concepts (e.g. split-apply-combine, data structures, object-oriented programming)
  • Solid statistics knowledge (hypothesis testing, ANOVA, chi-square tests, etc...)
  • Knowledge of NLP transfer learning, including word embedding models (gloVe, fastText, word2vec) and transformer models (Bert, SBert, HuggingFace, and GPT-x etc.)
  • Experience with natural language processing toolkits like NLTK, spaCy, Nvidia NeMo
  • Knowledge of microservices architecture and continuous delivery concepts in machine learning and related technologies such as helm, Docker and Kubernetes
  • Familiarity with Deep Learning techniques for NLP.
  • Familiarity with LLMs - using ollama & Langchain
  • Excellent verbal and written skills
  • Proven collaborator, thriving on teamwork
 
Preferred Qualifications
  • Master's or Doctor of Philosophy degree in Computer Science, Applied Math, Statistics, or a scientific field
  • Familiarity with cloud computing platforms (AWS, GCS, Azure)
  • Experience with automated supervision/surveillance/compliance tools
$166,000 - $214,000 a year
 
The above salary range represents Smarsh's good faith and reasonable estimate of the range of possible base compensation at the time of posting. Any applicable bonus programs will be discussed during the recruiting process.
 
The salary for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training.
 
Local cost of living assessments are done for each new hire at the time of offer.
About our culture

Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world's leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.
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