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Remote Mathematical Modeling Jobs in Oklahoma (NOW HIRING)

Architect modeling approaches that leverage modern techniques such as gradient boosting, deep ... Qualifications * Master's or PhD in Data Science, Statistics, Mathematics, Computer Science ...

Architect modeling approaches that leverage modern techniques such as gradient boosting, deep ... Qualifications * Master's or PhD in Data Science, Statistics, Mathematics, Computer Science ...

$50/hr

The analysis and alleviation of ethical flaws in generative models, including techniques for ... Mathematics, or related disciplines. Working Location Location flexible (Tokyo, NYC, remote) The ...

$50/hr

The analysis and alleviation of ethical flaws in generative models, including techniques for ... Mathematics, or related disciplines. Working Location Location flexible (Tokyo, NYC, remote) The ...

$50/hr

The analysis and alleviation of ethical flaws in generative models, including techniques for ... Mathematics, or related disciplines. Working Location Location flexible (Tokyo, NYC, remote) The ...

$50/hr

The analysis and alleviation of ethical flaws in generative models, including techniques for ... Mathematics, or related disciplines. Working Location Location flexible (Tokyo, NYC, remote) The ...

$50/hr

The analysis and alleviation of ethical flaws in generative models, including techniques for ... Mathematics, or related disciplines. Working Location Location flexible (Tokyo, NYC, remote) The ...

$50/hr

The analysis and alleviation of ethical flaws in generative models, including techniques for ... Mathematics, or related disciplines. Working Location Location flexible (Tokyo, NYC, remote) The ...

Engineer II (ILI Data Analysis)

Tulsa, OK · On-site +1

$104K - $125K/yr

The schedule is Hybrid, working from the Tulsa office Monday-Thursday and working remote on Friday ... Ability to: apply math and algebraic formulas * Data Modeling and visualization experience ...

$40/hr

Implement tooling and features to support machine learning model development and deployment under ... Currently pursuing a bachelor's degree or higher in Statistics, Mathematics, Computer Science ...

Showing results 21-40

Remote Mathematical Modeling information

What is remote mathematical modeling?

Remote mathematical modeling involves using mathematical equations and computational methods to represent real-world systems or processes, all while working from a location outside of a traditional office environment. Professionals in this field use tools like MATLAB, Python, or R to develop and analyze models for industries such as finance, engineering, healthcare, and environmental science. The remote aspect allows for flexible collaboration with teams worldwide through digital communication platforms. This role typically requires strong analytical skills, problem-solving abilities, and proficiency in mathematical software.

What are the key skills and qualifications needed to thrive as a remote mathematical modeler?

To thrive as a Remote Mathematical Modeler, you need a strong background in mathematics, statistics, and computational modeling, typically supported by a relevant degree such as mathematics, engineering, or physics. Proficiency with technical tools like MATLAB, R, Python, and specialized modeling software, as well as experience with data analysis and simulation platforms, is essential. Strong problem-solving, analytical thinking, and effective written communication skills set top performers apart in this role. These skills are crucial for developing accurate models, interpreting complex data remotely, and delivering clear insights to clients or stakeholders.

What are some common challenges faced by remote mathematical modelers, and how can they be addressed?

Remote mathematical modelers often encounter challenges such as limited real-time collaboration with colleagues, potential miscommunication regarding model requirements, and managing complex data sets independently. These can be addressed by utilizing collaborative tools like shared code repositories, regular virtual meetings, and clear documentation practices. Additionally, proactively seeking feedback and maintaining open channels of communication with stakeholders can help ensure alignment and successful project outcomes.

What are the most commonly searched types of Mathematical Modeling jobs in Oklahoma?

The most popular types of Mathematical Modeling jobs in Oklahoma are:

What are popular job titles related to Remote Mathematical Modeling jobs in Oklahoma?

For Remote Mathematical Modeling jobs in Oklahoma, the most frequently searched job titles are:

What cities in Oklahoma are hiring for Remote Mathematical Modeling jobs?

Cities in Oklahoma with the most Remote Mathematical Modeling job openings:

Principal Data Scientist

Sedgwick

Oklahoma City, OK • On-site, Remote

Full-time

Posted 8 days ago


Sedgwick rating

7.6

Company rating: 7.6 out of 10

Based on 328 frontline employees who took The Breakroom Quiz

219th of 315 rated insurance


Job description

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R71412

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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