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Remote Data Scientist Deep Learning Jobs in Oregon

Smarsh

Lead Data Scientist

OR · On-site +1

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 ...

SOSi

Senior Data Scientist

OR · On-site +1

Proficient in deep learning, supervised and unsupervised learning techniques, data wrangling, and ... Full remote flexibility. Working at SOSi All interested individuals will receive consideration and ...

SOSi

Data Scientist

OR · On-site +1

... learning and predictive modeling. * Proposed personnel possess the knowledge and capability to ... Full remote flexibility. Working at SOSi All interested individuals will receive consideration and ...

YipitData (Alternative)

Data Scientist, Corporate

OR · On-site +1

Rapid Growth : We compress years of learning into months * Merit Over Titles : Trust and ... Whether your deep expertise lies in refining core statistical baselines, optimizing heavy ...

YipitData

Data Scientist, Corporate

OR · On-site +1

Rapid Growth : We compress years of learning into months * Merit Over Titles : Trust and ... Whether your deep expertise lies in refining core statistical baselines, optimizing heavy ...

Sonatype

Data Scientist

OR · On-site +1

What you bring: * 5+ years of hands-on experience in applied data science, machine learning, AI ... Deep familiarity with modern LLM ecosystems, including OpenAI, Anthropic/Claude, Hugging Face, and ...

Nvidia

Deep Learning Compiler Engineer

OR · On-site +1

D. in Computer Science, Computer Engineering or a related field (or equivalent experience) * 3+ ... MLIR, LLVM, XLA, TVM and deep learning models and algorithms. With highly competitive salaries and ...

Nextdoor

Data Scientist - Search

OR · On-site +1

The Data Science group is made up of people from a diverse set of backgrounds and perspectives ... You are excited to go deep on ranking and recommendation systems, semantic retrieval, and the ...

Natera

Machine Learning Scientist, Multimodal AI

OR · On-site +1

Design, implement, and evaluate deep learning models across biomedical data modalities, including ... PhD in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics ...

CookUnity

Director, Data Science/ML

OR · On-site +1

Foster a culture of innovation, experimentation, and continuous learning within the data science ... Conduct deep-dive analyses on user behavior patterns to uncover opportunities for product ...

LP Careers Page

Lead Data Scientist, AdTech

OR · On-site +1

YOUR ROLE Own the full data science engine for a priority vertical, from business problem to ... LLMs / deep learning applied to personalization or content * Familiarity with Looker TOTAL ...

LP Careers Page

Staff Data Scientist, Marketing

OR · On-site +1

YOUR ROLE Own the full data science engine for a priority vertical, from business problem to ... LLMs / deep learning applied to personalization or content * Familiarity with Looker TOTAL ...

BetterHelp

Data Scientist

OR · On-site +1

As a Data Scientist at BetterHelp, you'll join a diverse team of licensed clinicians, engineers ... Remote work with regular in-person bonding experiences sponsored by the company * Competitive ...

Honor

Staff Data Scientist

Portland, OR · Remote

Deep technical depth in building, orchestrating, and establishing best practices for agentic ... We use national average to determine pay as we are a remote first company. Individual pay is based ...

Hitachi

Data Scientist I or II (MAD-BS-OR)

Hillsboro, OR · On-site +1

$121K - $167K/yr

Hybrid (+50% Remote) - Remote 60% / Onsite 40% EXPECTED PAY RANGE: Data Scientist I: $99,608 - $136 ... PRIMARY RESPONSIBILITIES * Hands-on development and write algorithms in machine learning ...

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Remote Data Scientist Deep Learning information

What is a remote data scientist specializing in deep learning?

Remote data scientists specializing in deep learning are professionals who use advanced machine learning techniques, particularly deep neural networks, to analyze large amounts of data and extract meaningful insights. They work from remote locations, leveraging digital tools to build, train, and deploy deep learning models for tasks such as image recognition, natural language processing, and predictive analytics. These experts collaborate with other team members virtually, contributing to projects in industries like healthcare, finance, and technology without needing to be physically present in an office.

What are the key skills and qualifications needed to thrive as a remote data scientist specializing in deep learning?

To thrive as a Remote Data Scientist specializing in Deep Learning, you need a strong background in mathematics, statistics, programming (especially Python), and experience with deep learning frameworks such as TensorFlow or PyTorch, often supported by a relevant degree. Familiarity with cloud platforms (e.g., AWS, GCP), version control systems like Git, and certifications in machine learning are highly beneficial. Strong analytical thinking, problem-solving abilities, and effective remote communication skills help you stand out in this position. These skills and qualities are essential for designing robust models, collaborating with distributed teams, and delivering impactful AI solutions.

How do remote data scientists specializing in deep learning typically collaborate with cross-functional teams?

Remote Data Scientists in Deep Learning often work closely with software engineers, product managers, and domain experts through virtual meetings, shared documentation, and version-controlled code repositories. They collaborate on defining project goals, sharing model insights, and integrating machine learning solutions into products. Effective communication and clear documentation are crucial, as team members may be in different time zones or have varying technical backgrounds. Tools like Slack, JIRA, and GitHub are commonly used to streamline collaboration and track progress.

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For Remote Data Scientist Deep Learning jobs in Oregon, the most frequently searched job titles are:

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Remote Data Scientist Deep Learning jobs near you

Lead Data Scientist

OR • On-site, Remote

Smarsh
Software Development • 1 - 5K employees
Learn more about Smarshexternal

Full-time

Re-posted 9 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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