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Senior Data Scientist Machine Learning Jobs in Nebraska

We're looking for a Sr. Data Scientist to join Snap Inc. What you'll do: * Apply your expertise in ... Conduct machine learning or statistical analyses, and build pragmatic, scalable, and statistically ...

We're looking for a Sr. Data Scientist to join Snap Inc. What you'll do: * Apply your expertise in ... Conduct machine learning or statistical analyses, and build pragmatic, scalable, and statistically ...

This role applies statistical, machine learning, and data analysis techniques to insurance data to ... Senior P&C Data Scientist also mentors lessexperienced team members and contributes to the ...

The Data Scientist may be responsible for any of the following tasks: Analyzing data that is ... machine learning models using state of the art Machine Learning and AI technologies, Visualize ...

As a Sr. Data Scientist, you will evaluate and improve Amgen's digital assets, collaborating as part of a multi-disciplinary team of scientists and engineers on a wide range of problems. The position ...

New

Data Scientist

Omaha, NE · On-site

$104.65 - $189.18/hr

Develop automated approaches leveraging artificial intelligence/machine learning (AI/ML) and ... Provide recommendations to senior leadership on data-driven strategies for OIE. * Define the means ...

Develop innovative data science solutions that utilize machine learning and deep learning ... to senior leadership. The Essentials * Masters in Computer Science, Mathematics, Physics ...

This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and ... data science, machine learning engineering, or data pipeline development. * Proficient in Python ...

This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and ... data science, machine learning engineering, or data pipeline development. * Proficient in Python ...

Job Title Senior Data Science Consultant, Insurance - Remote Requisition Number R7828 Senior Data ... This Data Scientist role offers the opportunity to help CSAA Insurance Group anticipate and prepare ...

Amentum is seeking an AI Modeling Specialist (Senior) to support Combatant Command Operations in ... Bachelor's degree in data science, computer science, artificial intelligence, machine learning ...

The Data Scientist is a highly analytical and business-savvy individual contributor who acts as an ... Design, develop, evaluate, and deploy state-of-the-art machine learning and deep learning models ...

The Data Scientist is a highly analytical and business-savvy individual contributor who acts as an ... Design, develop, evaluate, and deploy state-of-the-art machine learning and deep learning models ...

Data Scientist

Lincoln, NE · On-site

$110 - $160/hr

The Data Scientist is a highly analytical and business-savvy individual contributor who acts as an ... Design, develop, evaluate, and deploy state-of-the-art machine learning and deep learning models ...

New

The Data Scientist is a highly analytical and business-savvy individual contributor who acts as an ... Design, develop, evaluate, and deploy state-of-the-art machine learning and deep learning models ...

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Senior Data Scientist Machine Learning information

What does a senior data scientist specializing in machine learning do?

A Senior Data Scientist in Machine Learning leads the development, implementation, and optimization of advanced statistical and machine learning models to solve business problems. They analyze large, complex datasets, design predictive algorithms, and collaborate with cross-functional teams to integrate models into production systems. Additionally, they mentor junior data scientists, contribute to setting technical strategy, and often communicate findings to stakeholders to drive data-driven decision-making.

What are the key skills and qualifications needed to thrive as a senior data scientist in machine learning?

To thrive as a Senior Data Scientist in Machine Learning, you need advanced expertise in statistics, programming (Python or R), and machine learning algorithms, typically backed by a relevant degree (such as in computer science or mathematics) and several years of experience. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and cloud platforms (AWS, GCP, or Azure), as well as experience with big data technologies, is essential. Strong problem-solving, communication, and project leadership skills help drive impactful solutions and foster collaboration across teams. These skills ensure the successful design, deployment, and scaling of machine learning models that deliver business value.

How does a senior data scientist specializing in machine learning typically collaborate with cross-functional teams?

Senior Data Scientists in Machine Learning often work closely with product managers, software engineers, and business analysts to understand project goals and translate them into actionable data solutions. They are responsible for communicating complex technical concepts to non-technical stakeholders, ensuring that ML models align with business objectives. Collaboration frequently involves participating in regular strategy meetings, reviewing data pipelines with engineering teams, and providing insights that guide product development. This cross-disciplinary teamwork is essential for successfully deploying machine learning models into production environments.

What is the difference between Senior Data Scientist Machine Learning vs Data Scientist?

AspectSenior Data Scientist Machine LearningData Scientist
Required CredentialsMaster's or PhD in CS, Statistics, or related field; experience with ML frameworksBachelor's or Master's in relevant field; foundational knowledge of data analysis
Work EnvironmentAdvanced analytics teams, R&D, product developmentData analysis teams, business intelligence, reporting
Employer & Industry UsageTech companies, finance, healthcare, e-commerceSimilar industries, often entry to mid-level roles

The main difference is that Senior Data Scientist Machine Learning roles require more experience, advanced skills in ML frameworks, and often involve leading projects. Data Scientists typically focus on data analysis and reporting with less emphasis on complex ML models. Senior roles also tend to involve mentorship and strategic input.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Nebraska?

The most popular types of Data Scientist Machine Learning jobs in Nebraska are:

Infographic showing various Senior Data Scientist Machine Learning job openings in Nebraska as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Senior Data Scientist, Machine Learning

Firstnational

Omaha, NE

$89K - $148K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 4 days ago


Job description

At FNBO, our employees are the heart of our story-and we're committed to their success! Please see below the details of this career opportunity and how it fits into our organization's success.

Summary of the Job:

The Senior Data Scientist, Machine Learning is responsible for the development, implementation, and operationalization of machine learning (ML) and artificial intelligence (AI) models to drive business impact. This role involves working with a team of highly quantitative data scientists and working with a cross-functional team of engineers, analysts, and business users to deliver innovative solutions, optimizing decision-making processes, and enabling automation at scale. The role will ensure that models are effectively managed in accordance with the model risk management governance and integrated into business workflows and deliver measurable value.

About This Role:

Direct Scope and Accountabilities

Model Development and Deployment:

  • Oversee the end-to-end lifecycle of ML/AI models, from ideation and development to deployment and monitoring, including but not limited to loss prediction, fraud detection, marketing optimization and customer feedback mining.
  • Ensure the scalability, reliability, and robustness of deployed models.
  • Establish best practices for model development, including feature engineering, hyperparameter tuning, and model evaluation.
  • Work with key stakeholders (e.g., FNIT, business partners) to implement the model and drive business value at a timely manner.

Model Performance Monitoring:

  • Define KPIs to measure the model performance and impacts.
  • Implement monitoring systems to ensure model accuracy, relevance, and efficiency over time.
  • Continuously refine and optimize models based on feedback and performance metrics.

Model Management and Governance:

  • Ensure the model development and monitoring practices in compliance with the FNNI model risk management team.
  • Effective communicate modeling approaches and results to external regulators and proactively address their suggestions and comments.
  • Monitor and mitigate risks associated with model bias, drift, and interpretability.
  • Maintain transparency and accountability in the deployment of ML/AI solutions.

Innovation:

  • Evaluate and implement cutting-edge tools, frameworks, and platforms for ML/AI development and deployment.
  • Stay updated on emerging trends, technologies, and best practices in data science.
  • Drive experimentation and pilot programs to test innovative approaches and solutions.

Collaboration and Stakeholder Engagement:

  • Partner with business units to understand their challenges and deliver tailored modeling solutions.
  • Effectively deliver business values to key stakeholders through innovative ML/AI models.
  • Effectively communicate complex technical concepts to non-technical stakeholders in a clear and actionable manner.
  • Build and maintain strategic relationships with external partners, vendors, and research institutions.

Key Performance Indicators (KPIs):

  • Model Performance: Accuracy, precision, recall, and other metrics for deployed models.
  • Business Impact: Measurable improvements in key business metrics influenced by models.
  • Operational Efficiency: Reduction in manual processes and increased automation.
  • Model governance: Compliance with ethical standards and regulatory requirements.

The Ideal Candidate for This Role:

Qualifications

Education:

  • Master's degree or higher in Data Science, Computer Science, Statistics, Mathematics, AI, or a related field.

Experience:

  • Minimum of 3 years of experience in data science or related fields.
  • Proven track record of developing and deploying ML/AI models that deliver business impact.
  • Experience managing cross-functional teams and complex projects.
  • Proven experience to effective communicate modeling approaches and results to external regulators and proactively address their suggestions and comments.

Skills and Competencies:

  • Expertise in machine learning, deep learning, and statistical modeling techniques.
  • Proficiency in programming languages such as Python, R, and SQL, as well as ML/AI frameworks like Claude.
  • Strong knowledge of data visualization tools (e.g., Power BI) and cloud platforms (e.g., AWS, Snowflake).
  • Exceptional leadership, communication, and stakeholder management skills.
  • Analytical and strategic thinking abilities with a focus on measurable outcomes.
Candidates must possess unrestricted work authorization and not require future sponsorship.

Compensation:

Compensation range (base pay): $89,828.00-$148,215.00

This role may have a specific starting pay within this range.

Final compensation offer to candidate may vary from posted hiring range based upon work experience, education, and/or skill level.

Work Environment:

It is anticipated that the incumbent in this role will work in a hybrid capacity, balancing in-person collaboration three (3) days a week with remote flexibility two (2) days a week. As part of our team, you'll experience the energy and relationship-building of face-to-face collaboration while still enjoying the flexibility of remote workdays. We provide the tools and technology to ensure seamless transitions between work environments, supporting your productivity wherever you are. Please note that work location is subject to change based on business needs.

Benefits Overview:

We offer a variety of benefits designed to keep you and your family physically and financially healthy. Not only do we offer a competitive salary and work-life balance, we offer benefits to match your needs:

  • Medical, Dental, Vision Insurance

  • 401k, With Matching Contributions

  • Time Off Programs

  • Health Savings Account (HSA)/Dependent Care

  • Employee Banking

  • Growth Opportunities

  • Tuition Assistance

  • Short-Term/Long-Term Disability Insurance

Learn more about FNBO benefits here: https://www.fnbo.com/careers/benefits/.

For additional information regarding compensation and benefits, e-mail FNBO at TAGAdmin@fnni.com. To ensure you receive a response, include the number of this job (listed below) in the subject line of your message.

Job number: R-20261507

Equal Opportunity & Belonging:

FNBO believes that the quality of our employee experience is at the heart of our customer experience. One key pillar of our intended employee experience is Belonging. Belonging means we are committed to fostering a workplace culture where employees of all backgrounds feel valued, recognized, and empowered to be their authentic selves-no matter their role or where they are in their journey.

Learn more here.

FNBO is an equal opportunity employer for all employees and applicants and makes employment decisions without regard to status or identity.

Click here to download 'EEO is The Law' Self-Print Poster

Click here to download 'EEO is The Law' Supplement for Federal Contractors

Click here to download 'EEO is The Law' GINA Supplement

FNBO is an Equal Opportunity/Affirmative Action/Veterans/Disability Employer - Member FDIC

FNBO follows federal law regarding the use of marijuana (this applies to all non-California applicants)

Application Deadline:

All our jobs will be posted for a minimum of 5 calendar days. Job postings may come down prior to 5 calendar days based on volume of applicants.