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Data Annotation Tech Remote Jobs in Oregon (NOW HIRING)

Smarsh

Lead Data Scientist

OR · On-site +1

Data annotation and quality review * Exploratory data analysis and model fail state analysis ... We use the latest in AI/ML technology to help our customers break new ground at scale. We are a ...

Waabi

Senior / Staff Software Engineer, Web Tools

OR · On-site +1

$141K - $249K/yr

... tools, data annotation tools, dataset curation tools, result comparison tools, and more ... Waabi is a technology start-up building technologies to transform the way the world moves. Join our ...

ConnectWise

IT Enterprise Data Architect

OR · On-site +1

The IT Enterprise Data Architect is responsible for defining, governing, and evolving ConnectWise ... Onsite, Hybrid, or Remote depending on location. * Occasional travel may be required to support ...

micro1 AI

AI Trainer - Microbiology Expert

Eugene, OR · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

micro1 AI

AI Trainer - Microbiology Expert

Bend, OR · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

micro1 AI

AI Trainer - Microbiology Expert

Salem, OR · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

micro1 AI

AI Trainer - Microbiology Expert

Gresham, OR · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

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All JobsData Annotation Tech JobsData Annotation Tech Remote JobsData Annotation Tech Remote Jobs in Oregon

Data Annotation Tech Remote information

What is the difference between Data Annotation Tech Remote vs Data Labeling Specialist?

AspectData Annotation Tech RemoteData Labeling Specialist
CredentialsBasic technical skills, sometimes certifications in data annotation toolsSimilar credentials, often with experience in labeling software
Work EnvironmentRemote, often freelance or contract-basedRemote or on-site, depending on employer
Industry UsageUsed across AI, machine learning, and data science companiesCommon in AI, autonomous vehicles, and tech firms

Both roles involve labeling data for machine learning models, with similar credentials and remote work options. The main difference lies in job titles used by employers, but their responsibilities and industry applications overlap significantly.

What is a data annotation tech remote?

Data Annotation Tech Remote jobs involve working from home or another remote location to label, tag, or classify data such as text, images, audio, or video. This work is essential for training and improving artificial intelligence and machine learning models. Data annotators use specialized software tools to accurately identify and categorize data according to specific guidelines provided by employers. These roles require attention to detail, consistency, and sometimes subject-matter expertise, depending on the project. Remote data annotation jobs are popular because they often offer flexible schedules and the ability to work from anywhere.

What are some common challenges faced by remote data annotation techs, and how can they be addressed?

Remote Data Annotation Technicians often encounter challenges such as maintaining consistent annotation quality, managing repetitive tasks, and ensuring clear communication with team leads or project managers. To address these, it's helpful to establish a structured daily routine, use collaboration tools to stay connected with the team, and regularly review project guidelines to ensure accuracy. Many organizations also provide feedback loops and quality assurance checks, so being proactive in seeking feedback can help improve performance and job satisfaction.

How much do remote data annotation tech jobs pay?

Remote data annotation technician jobs typically pay between $12 and $20 per hour, depending on experience, skill level, and the complexity of the annotation tasks. Some positions may offer additional benefits or flexible schedules, and pay rates can vary based on the employer and geographic location of the company. Entry-level roles often start at the lower end of the pay scale, while experienced annotators or those with specialized skills may earn higher wages.

What are the key skills and qualifications needed to thrive as a data annotation tech remote?

To excel as a Data Annotation Tech (Remote), you need attention to detail, basic computer literacy, and familiarity with data labeling practices, often supported by a high school diploma or equivalent. Proficiency with annotation tools such as Labelbox, Supervisely, or proprietary platforms is typically required, and training in data privacy or quality assurance may be beneficial. Strong communication, time management, and the ability to focus independently are standout soft skills for this remote role. These competencies are crucial to ensure accurate, high-quality data labeling that directly impacts the effectiveness of AI and machine learning models.

What are the most commonly searched types of Data Annotation Tech jobs in Oregon?

The most popular types of Data Annotation Tech jobs in Oregon are:

What are popular job titles related to Data Annotation Tech Remote jobs in Oregon?

For Data Annotation Tech Remote jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Data Annotation Tech Remote jobs in Oregon look for?

The top searched job categories for Data Annotation Tech Remote jobs in Oregon are:

Data Annotation Tech Remote jobs near you
Infographic showing various Data Annotation Tech Remote 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.

Lead Data Scientist

Smarsh

OR • On-site, Remote

Full-time

Re-posted yesterday

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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