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Remote Data Scientist Deep Learning Jobs in Nebraska

Deep expertise in machine learning algorithms, statistical modeling techniques, and predictive ... Strong mentoring and technical leadership capabilities. #LI-TS1 #remote Sedgwick is an Equal ...

New

Deep expertise in machine learning algorithms, statistical modeling techniques, and predictive ... Strong mentoring and technical leadership capabilities. #LI-TS1 #remote Sedgwick is an Equal ...

New

Remote Categories: Information Technology Join Mutual of Omaha as were looking for a Data Science ... A strong background in machine learning and statistical analysis, with the ability to validate ...

... deep learning fundamentals. Ability to explain linear regression, decision trees, random forests, support vector machines, and neural network architectures while preparing students for data science ...

... deep learning fundamentals. Ability to explain linear regression, decision trees, random forests, support vector machines, and neural network architectures while preparing students for data science ...

Decision Scientist

Lincoln, NE · On-site +1

$40/hr

... remote work and setting your own schedule. We are looking for experienced quantitative ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

$150K - $180K/yr

Data Science and ML experience - (R, Python, Deep Learning Frameworks etc.) * Integration Products ... Employee Resource Groups EEO/VEVRAA #LI-MH2 #LI-remote

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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, and why are they important?

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 are remote data scientists 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 most commonly searched types of Data Scientist Deep Learning jobs in Nebraska? The most popular types of Data Scientist Deep Learning jobs in Nebraska are:
What are popular job titles related to Remote Data Scientist Deep Learning jobs in Nebraska? For Remote Data Scientist Deep Learning jobs in Nebraska, the most frequently searched job titles are:
Principal Data Scientist

Principal Data Scientist

Sedgwick

Omaha, NE • On-site, Remote

Other

This job post has expired today. Applications are no longer accepted.


Sedgwick rating

7.5

Company rating: 7.5 out of 10

Based on 305 frontline employees who took The Breakroom Quiz

195th of 258 rated insurance


Job description

By joining Sedgwick, you'll be part of something truly meaningful. It’s what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there’s no limit to what you can achieve.

Newsweek Recognizes Sedgwick as America’s Greatest Workplaces National Top Companies

Certified as a Great Place to Work®

Fortune Best Workplaces in Financial Services & Insurance

Principal Data Scientist

Job Responsibilities

  • Lead the design and development of advanced statistical and machine learning models that improve claims outcomes, operational efficiency, and risk management.

  • Serve as the technical authority for complex modeling initiatives including fraud detection, claims severity prediction, litigation risk modeling, and recovery optimization.

  • Develop predictive and prescriptive models using structured and unstructured claims data, including adjuster notes, medical records, and policy documentation.

  • Architect modeling approaches that leverage modern techniques such as gradient boosting, deep learning, NLP, anomaly detection, and probabilistic modeling.

  • Partner with AI Engineering teams to productionize models and integrate them into enterprise AI platforms and operational systems.

  • Design feature engineering strategies and modeling pipelines using large-scale enterprise datasets.

  • Establish best practices for model development, experimentation, validation, and reproducibility.

  • Lead advanced analytical techniques such as causal inference, scenario simulation, and risk scoring methodologies.

  • Build and maintain model evaluation frameworks that measure accuracy, bias, stability, and business impact.

  • Monitor deployed models for drift, degradation, and changing data distributions, and recommend recalibration strategies.

  • Provide technical guidance to data scientists and analysts across the organization.

  • Mentor junior team members on statistical methods, machine learning techniques, and analytical rigor.

  • Translate complex analytical findings into clear, actionable insights for business leaders and operational teams.

  • Collaborate with Claims Operations, Finance, Risk, and IT stakeholders to identify high-impact analytical opportunities.

  • Evaluate external data sources and third-party analytical solutions that enhance predictive capabilities.

  • Ensure analytical methodologies align with enterprise governance standards and regulatory expectations.

  • Contribute to Sedgwick’s broader AI and advanced analytics strategy by identifying emerging technologies and modeling approaches.

  • Lead research and innovation initiatives that advance Sedgwick’s predictive analytics capabilities.

Qualifications

  • Master’s or PhD in Data Science, Statistics, Mathematics, Computer Science, Economics, or related quantitative discipline.

  • 8–12+ years of experience in data science, statistical modeling, or advanced analytics roles.

  • Deep expertise in machine learning algorithms, statistical modeling techniques, and predictive analytics methodologies.

  • Strong programming skills in Python, R, or similar analytical languages.

  • Extensive experience working with large, complex datasets in enterprise environments.

  • Proven experience designing and implementing end-to-end modeling pipelines.

  • Strong understanding of model validation, feature engineering, and performance evaluation techniques.

  • Experience collaborating with engineering teams to deploy models into production systems.

  • Familiarity with distributed data processing tools and modern data platforms preferred.

  • Experience in insurance, claims management, healthcare, or financial services analytics preferred.

  • Ability to communicate advanced analytical concepts to both technical and non-technical stakeholders.

  • Demonstrated ability to lead complex analytical initiatives that drive measurable business value.

  • Strong mentoring and technical leadership capabilities.

#LI-TS1 #remote

Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace.

If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.

Sedgwick is the world’s leading risk and claims administration partner, which helps clients thrive by navigating the unexpected. The company’s expertise, combined with the most advanced AI-enabled technology available, sets the standard for solutions in claims administration, loss adjusting, benefits administration, and product recall. With over 33,000 colleagues and 10,000 clients across 80 countries, Sedgwick provides unmatched perspective, caring that counts, and solutions for the rapidly changing and complex risk landscape. For more, see sedgwick.com


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