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Senior Data Scientist Machine Learning Jobs in Alaska

Sedgwick

Senior and Applied/Agentic AI Engineer

Minto, AK

$108K - $148K/yr

Design secure tool integration layers connecting agents to claims systems, policy platforms, data ... AI engineering, machine learning systems, or distributed software architecture. 3-5+ years ...

6AM City

Senior Clinical Data Manager

False Pass, AK

As part of the Medical and Scientific Affairs group, an integral delivery unit within the Global ... Learning & Development Programs Paid Educational Assistance Center Valley, PA and Westborough, MA ...

6AM City

Senior Clinical Data Manager

False Pass, AK · On-site

As part of the Medical and Scientific Affairs group, an integral delivery unit within the Global ... Learning & Development Programs Paid Educational Assistance Center Valley, PA and Westborough, MA ...

York Risk Services

Senior Engineer - LLMOps & MLOps

Minto, AK · On-site +1

$108K - $148K/yr

... Services & Insurance Senior Engineer - LLMOps & MLOps Role Overview This is a high-stakes ... Data Science Engineering: Support the data science lifecycle by automating feature stores, feature ...

Sedgwick

Senior Engineer - LLMOps & MLOps

Minto, AK · On-site +1

$108K - $148K/yr

... Services & Insurance Senior Engineer - LLMOps & MLOps Role Overview This is a high-stakes ... Data Science Engineering: Support the data science lifecycle by automating feature stores, feature ...

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All JobsData Scientist Machine Learning JobsSenior Data Scientist Machine Learning JobsSenior Data Scientist Machine Learning Jobs in Alaska

Senior Data Scientist Machine Learning information

See Alaska salary details

$101.2K

$137.9K

$162.1K

How much do senior data scientist machine learning jobs pay per year?

As of Aug 9, 2026, the average yearly pay for senior data scientist machine learning in Alaska is $137,907.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,319.00 and $152,548.00 per year, depending on experience, location, and employer.

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 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.

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 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 cities in Alaska are hiring for Senior Data Scientist Machine Learning jobs? Cities in Alaska with the most Senior Data Scientist Machine Learning job openings:
Senior Data Scientist Machine Learning jobs near you

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Fairbanks, AK • On-site

Other

Re-posted 18 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply