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Remote Data Scientist Deep Learning Jobs in Delaware

Reco

Security Researcher

Wilmington, DE · On-site +1

Dive deep into terabytes of SaaS Application data to identify new attack vectors, emerging threats ... Collaborate with security researchers and data scientists to define new threat detection strategies ...

Best Egg

Senior Credit Risk Analyst -Verifications

Wilmington, DE · On-site +1

$120K - $140K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Partner with Product, Data Science, Fraud, and Credit Underwriting Turn analysis into clear, high ... Deep experience with income verification vendors and workflows * Familiarity with credit risk ...

Truveris

Customer Success Director

Wilmington, DE · On-site +1

$120K - $150K/yr

... • Remote Role with Travel About Truveris Truveris is a pharmacy cost containment company ... Our proprietary, data-driven technology and deep industry expertise empower smarter pharmacy ...

Kemper

SVP, Chief Technology Officer (CTO)

Dover, DE · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... IL, Remote-MI, Remote-NJ, St. Louis, Missouri Details Kemper is one of the nation's leading ... Enterprise Data Engineering * Artificial Intelligence & Intelligent Automation * Enterprise ...

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Remote Data Scientist Deep Learning information

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.

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.

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Remote Data Scientist Deep Learning jobs near you

Security Researcher

Reco

Wilmington, DE • On-site, Remote

Full-time

Re-posted 10 days ago

Job description

Description
Reco is a fast-growing SaaS security company that helps organizations secure their SaaS and AI environments by detecting identity-based threats and risky configurations.
We are looking for a Threat Detection Engineer to analyze large-scale SaaS security data, investigate incidents, and develop advanced threat detection strategies.
You will work closely with security researchers and customers to identify emerging threats and improve detection capabilities across SaaS environments.
Responsibilities
  • Threat Analysis and Research: Dive deep into terabytes of SaaS Application data to identify new attack vectors, emerging threats, and vulnerabilities across various attack surfaces.
  • Stay up-to-date with the latest cybersecurity trends and contribute to the development of cutting-edge threat detection methodologies.
  • Incident Investigation: Utilize your technical prowess to investigate complex SaaS & AI security incidents, analyzing data from diverse SaaS applications to uncover the root causes and methods of attack.
  • False Positive Reduction: Leverage your expertise in data analysis and correlation to fine-tune detection rules and algorithms, minimizing false positives and enhancing the accuracy of our platform's threat alerts.
  • Thought Leadership and Community Engagement: Drive thought leadership initiatives by creating technical blog posts, delivering webinars, and speaking at conferences to share insights, educate the community, and enhance the company's reputation in the cybersecurity landscape.
  • Be at the forefront of the Reco mission and work closely with Reco customers regarding cyber security investigations and incidents detected in their environments
  • Collaborate with security researchers and data scientists to define new threat detection strategies based on SaaS attack vectors and industry trends.
  • Continuously monitor and analyze SaaS attack techniques, adapting security posture to evolving threats.
  • Work with APIs and integrations to ingest security logs from various SaaS platforms, correlating signals to detect real threats.

Requirements
  • A background of at least 5 years in cybersecurity, preferably in SOC, SIEM, Threat Intelligence, or Cloud Security
  • Experience with SaaS security challenges, such as shadow IT, OAuth risks, IDP misconfigurations, and excessive permissions.
  • Hands-on experience with security data analysis, including large-scale log processing, anomaly detection, and behavioral analytics.
  • Proficiency in SQL (e.g., ClickHouse) for querying security events and correlating threat indicators.
  • Strong understanding of identity-based attacks, insider threats, and SOC detection methodologies.
  • Familiarity with SIEM and XDR solutions (e.g., Splunk, Sentinel, Chronicle) and their role in modern detection engineering.
  • Strong problem-solving and analytical skills to triage security incidents and optimize detection rules.

Advantages:
  • Familiarity with SaaS security best practices, including least-privilege access, OAuth governance, and SSPM.
  • Knowledge of SaaS security frameworks (e.g., SSPM, CASB).
  • Experience with IDP security (Okta, Azure AD, Google IAM) and detecting identity-related SaaS threats.
  • Hands-on experience with Threat Hunting and / or Detection engineering in SaaS environments.
  • Understanding of SaaS API security and experience analyzing integrations with third-party applications.

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