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Remote Data Scientist Machine Learning Jobs in Kentucky

Lead the design and development of advanced statistical and machine learning models that improve ... Strong mentoring and technical leadership capabilities. #LI-TS1 #remote Sedgwick is an Equal ...

Lead and oversee the development of advanced machine learning models, ensuring their seamless ... per week remote/home. Office Location Options: * Louisville, KY * Boston, MA * New York, NY

Lead and oversee the development of advanced machine learning models, ensuring their seamless ... per week remote/home. Office Location Options: * Louisville, KY * Boston, MA * New York, NY

Lead and oversee the development of advanced machine learning models, ensuring their seamless ... per week remote/home. Office Location Options: * Louisville, KY * Boston, MA * New York, NY

Lead Data Scientist

Lexington, KY · On-site +1

$180K - $200K/yr

Enterprise AI Location: 100% Remote Sponsorship: Available for exceptional candidates About the ... D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or related field ...

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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 ...

Fraud Model Analyst

Louisville, KY · On-site +1

$45K - $103.50K/yr

... remote work in select geographic locations, subject to approval by PNC. If approved, work must be ... Data Science, Machine Learning (ML) Competencies Data Architecture, Data Mining, Disruptive ...

Data Engineer (Remote)

Canton, MA · On-site +1

$121.10K - $145.40K/yr

Support deployment and operationalization of machine learning models by integrating pipelines with ... Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related ...

Data Engineer (Remote)

Louisville, KY · On-site +1

$104.80K - $125.80K/yr

Support deployment and operationalization of machine learning models by integrating pipelines with ... Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related ...

Data Engineer (Remote)

Louisville, KY · On-site +1

$104.80K - $125.80K/yr

Support deployment and operationalization of machine learning models by integrating pipelines with ... Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related ...

Remote Reference ID: JN -052026-106781 Date Posted: 05/05/2026 Shortcut: * Description ... Exposure to data science or machine learning applications. * Experience with MLOps or model ...

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Remote Data Scientist Machine Learning information

What are the key skills and qualifications needed to thrive as a Remote Data Scientist specializing in Machine Learning, and why are they important?

To excel as a Remote Data Scientist in Machine Learning, you need a solid background in statistics, programming (typically Python or R), and a degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as TensorFlow, scikit-learn, PyTorch, and experience with cloud platforms like AWS or Azure are often required, along with relevant certifications. Strong problem-solving skills, effective communication, and the ability to work independently are crucial soft skills for remote collaboration and translating insights for diverse stakeholders. These competencies ensure the development of robust models, clear communication of findings, and successful project delivery in a distributed work environment.

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

Remote data scientists in machine learning often work closely with product managers, engineers, and business analysts through virtual meetings, collaborative platforms, and shared documentation tools. They regularly participate in sprint planning, code reviews, and brainstorming sessions to ensure alignment with project goals. Effective communication and proactive updates are essential for overcoming the challenges of remote collaboration and maintaining project momentum. Building strong relationships with team members across different time zones helps foster innovation and ensures that machine learning solutions are well-integrated into broader business objectives.

What does a Remote Data Scientist specializing in Machine Learning do?

A Remote Data Scientist specializing in Machine Learning uses advanced statistical techniques and programming skills to analyze large datasets and build predictive models, all while working from a remote location. They design, develop, and deploy machine learning algorithms to solve business problems, such as forecasting trends or automating processes. Their work often involves data cleaning, feature engineering, model selection, and collaborating with cross-functional teams to integrate these models into products or services. Remote data scientists typically use tools like Python, R, and cloud-based platforms to perform their tasks efficiently.

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

AspectRemote Data Scientist Machine LearningRemote Data Scientist
Required CredentialsMaster's or PhD in Data Science, Computer Science, or related field; experience with ML frameworksSimilar educational background; may focus more on statistical analysis and data visualization
Work EnvironmentPrimarily involves developing ML models, coding in Python/R, and deploying algorithmsFocuses on data analysis, reporting, and insights generation, often with less emphasis on ML deployment
Employer & Industry UsageUsed in tech, finance, healthcare for predictive modeling and automationCommon across various industries for data analysis and business intelligence

While both roles require strong analytical skills and similar educational backgrounds, Remote Data Scientist Machine Learning specializes in developing and deploying machine learning models, whereas Remote Data Scientist focuses more on data analysis and reporting. The ML role often involves coding and algorithm development, making it more technical in nature.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Kentucky? The most popular types of Data Scientist Machine Learning jobs in Kentucky are:
What are popular job titles related to Remote Data Scientist Machine Learning jobs in Kentucky? For Remote Data Scientist Machine Learning jobs in Kentucky, the most frequently searched job titles are:
What job categories do people searching Remote Data Scientist Machine Learning jobs in Kentucky look for? The top searched job categories for Remote Data Scientist Machine Learning jobs in Kentucky are:
Principal Data Scientist

Principal Data Scientist

Sedgwick

Louisville, KY • 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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