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Flexible Data Annotation Analyst 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 * Contribute to model governance, documentation, and explainability frameworks aligned with internal and ...

FloVision Solutions

Machine Learning Engineer

OR · On-site +1

Collaborate with the annotation team to improve data quality, labeling practices, and machine ... Strong analytical, programming, and problem-solving skills * Ability to work effectively in a fast ...

New

TSMG

Robot Teleoperator (AI & Robotics)

Salem, OR · On-site

Support data annotation and quality validation activities * Maintain accurate operational records ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

TSMG

Robot Teleoperator (AI & Robotics)

Salem, OR

Support data annotation and quality validation activities * Maintain accurate operational records ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Klamath Basin Behavioral Health (KBBH)

OR · On-site

$51K - $64K/yr

Flexible Spending Account (FSA) * Health Savings Account (HSA) * Employee Assistance Program (EAP ... Klamath Basin Behavioral Health is seeking a QPI Data Analyst I to help turn data into clear ...

Parachute Health

Lead Data Analyst

OR · On-site +1

$160K - $200K/yr

About the Role The Lead Data Analyst is the senior individual contributor on our Data Analytics ... Flexible Vacation Policy * Summer Fridays: 5 additional Fridays off during the summer (separate ...

Socket.dev

BMPS Data Analyst

Grants Pass, OR · On-site

$70 - $95/hr

BMPS Data Analyst at AllCare Health with the Benefit Management & Pharmacy Services department in ... flexible schedule options. Summary of the Position: This position is responsible for supporting ...

Allcare-Health

BMPS Data Analyst

Grants Pass, OR · On-site

$76.96 - $83.20/hr

... Hourly BMPS Data Analyst at AllCare Health with the Benefit Management & Pharmacy Services ... flexible schedule options. Summary of the Position This position is responsible for supporting ...

Agility Robotics

Staff AI Engineer, Perception

Salem, OR · On-site

$207K - $323K/yr

Experience with MLOps such as (but not limited to) data annotation services, data storage, model ... Flexible, unlimited PTO and 12 company holidays, including a winter shutdown. * Non-Exempt ...

Agility Robotics

Staff AI Engineer, Perception

Salem, OR · On-site +1

$207K - $323K/yr

Experience with MLOps such as (but not limited to) data annotation services, data storage, model ... Flexible, unlimited PTO and 12 company holidays, including a winter shutdown. * Non-Exempt ...

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Flexible Data Annotation Analyst information

What is a flexible data annotation analyst?

A Flexible Data Annotation Analyst is a professional responsible for labeling, categorizing, and tagging data—such as text, images, audio, or video—to prepare it for use in machine learning and artificial intelligence projects. The 'flexible' aspect typically means the role allows for remote work, adjustable hours, or project-based assignments. Analysts use specific tools and follow detailed guidelines to ensure data quality and consistency. This role is crucial for training accurate AI models, as well-annotated data helps improve the performance of automated systems.

What are the key skills and qualifications needed to thrive as a flexible data annotation analyst?

To thrive as a Flexible Data Annotation Analyst, you need keen attention to detail, analytical thinking, and a basic understanding of data labeling processes, often supported by a high school diploma or relevant experience. Familiarity with annotation tools such as Labelbox, Prodigy, or similar platforms, as well as basic proficiency in spreadsheet software, is typically required. Strong time management, adaptability, and clear communication skills help you deliver accurate results and work effectively with remote teams. These abilities ensure high-quality, consistent data labeling that is critical for training reliable machine learning models.

How does a flexible data annotation analyst typically collaborate with other teams to ensure data quality?

As a Flexible Data Annotation Analyst, you will frequently interact with data scientists, machine learning engineers, and project managers to clarify annotation guidelines and resolve ambiguities in the data. Collaboration often involves participating in virtual meetings, providing feedback on annotation tools, and reporting inconsistencies or uncertainties encountered during the labeling process. This teamwork ensures that annotated datasets meet project standards and contribute to high-quality machine learning outcomes. Regular communication and openness to feedback are key to success in this collaborative environment.

Can I work as a flexible data annotation analyst with no experience?

Flexible data annotation analyst roles often do not require prior experience, as training is typically provided to teach the necessary skills and tools. Basic computer literacy and attention to detail are usually sufficient to start, making it accessible for beginners interested in data labeling tasks.

Do data annotation jobs offer flexible hours?

Data annotation jobs often offer flexible hours, allowing workers to choose when they complete tasks, especially in freelance or remote roles. However, some positions may have deadlines or specific schedules depending on the employer or project requirements.

Does data annotation actually pay well?

Data annotation analysts typically earn hourly wages that are close to minimum wage or slightly above, depending on the platform and complexity of tasks. Pay rates can vary based on experience, skill level, and the employer, but generally, it is not considered a high-paying role. Many positions are freelance or part-time, which can impact overall earnings.

Is it hard to get hired for a flexible data annotation analyst?

Getting hired as a flexible data annotation analyst generally depends on having basic computer skills, attention to detail, and familiarity with annotation tools. Many positions are entry-level and may not require extensive experience, making the role accessible to a wide range of candidates. However, competition can vary based on the employer and location, and some roles may prefer candidates with prior experience or specific technical knowledge.

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

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

What are popular job titles related to Flexible Data Annotation Analyst jobs in Oregon?

For Flexible Data Annotation Analyst jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Flexible Data Annotation Analyst jobs in Oregon look for?

The top searched job categories for Flexible Data Annotation Analyst jobs in Oregon are:

What cities in Oregon are hiring for Flexible Data Annotation Analyst jobs?

Cities in Oregon with the most Flexible Data Annotation Analyst job openings:

Flexible Data Annotation Analyst jobs near you

Lead Data Scientist

Smarsh

OR • On-site, Remote

Full-time

Re-posted 7 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
$180,000 - $200,000 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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