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Scientific Machine Learning Jobs in Alaska (NOW HIRING)

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Learn and understand a large body of research in deep learning and machine learning * Participate ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Learn and understand a large body of research in deep learning and machine learning * Participate ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Learn and understand a large body of research in deep learning and machine learning * Participate ...

micro1 AI

AI Trainer - Microbiology Expert

Anchorage, AK · Remote

$70 - $90/hr

Prior experience developing or applying rubrics in scientific or educational contexts. * Experience with AI, machine learning, or annotation projects related to biology or microbiology. * Advanced ...

University of Alaska

Post Doctoral Fellow

Fairbanks, AK · On-site

$50K - $68K/yr

... machine learning, remote sensing, image analysis, geodesy, or the development of real-time monitoring and detection systems is desirable. The candidate should enjoy solving complex scientific ...

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Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

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

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Alaska?

For Scientific Machine Learning jobs in Alaska, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in Alaska look for?

The top searched job categories for Scientific Machine Learning jobs in Alaska are:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Alaska as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

AI Data Scientist

Tanaq Technical Services LLC

Anchorage, AK • On-site

Full-time

Posted 7 days ago

Job description

Description:


Overview


Tanaq Technical Services (TTS), a division of St. George Tanaq (SGT)Corporation, is an 8(a) Alaskan Native Small Business that specializes in delivering Enterprise Integrated Technology Solutions and Support Services to the Federal Government. Our teams combine modern engineering, secure cloud architecture, and emerging technologies including AI/ML to improve customer experiences, operational efficiencies, and mission outcomes. We pride ourselves on being Mission Driven and People Focused delivering emerging technologies seamlessly for our clients. People Focused. To learn more about us, visit https://tanaq.com/tanaq-technical-services.


About the Role


We are seeking a highly skilled AI Data Scientist to support the Department of Housing and Urban Development’s Office of the Chief Information Officer (HUD OCIO).


The AI Data Scientist will analyze, model, and simulate data supporting HUD AI/ML proofs of concept and pilots. Additionally, this role will be responsible for designing, developing, and operationalizing advanced analytics, machine learning models, predictive simulations, and AI-driven solutions that support mission-critical business objectives.


The ideal candidate combines deep technical expertise in data science, machine learning, and statistical modeling with the ability to translate complex business problems into scalable, production-ready solutions. You will work across multidisciplinary teams including engineering, AI architects, security professionals, DevOps teams, and business stakeholders to deliver innovative and trustworthy AI capabilities.


This position offers the opportunity to influence enterprise-scale AI initiatives, develop advanced decision-support solutions, and help establish best practices for responsible AI, model governance, and data-driven innovation.


This is a remote position supporting a federal government contract that requires a federal background check and NACI clearance. Candidates must reside in the United States. An estimated 10-15% annual travel within the U.S. will be required.


Responsibilities


Data Science & Machine Learning

  • Develop, train, validate, and deploy machine learning models, predictive analytics solutions, and statistical frameworks.
  • Design and implement simulations, forecasting models, optimization techniques, and decision-support systems.
  • Analyze structured and unstructured datasets to identify patterns, trends, risks, and opportunities.
  • Conduct feature engineering, data preparation, cleansing, transformation, and quality assessments to support AI and analytics initiatives.
  • Evaluate model performance and continuously refine algorithms to improve accuracy, reliability, and business impact.

AI & Advanced Analytics

  • Support the development of AI-enabled solutions utilizing machine learning, generative AI, large language models (LLMs), and emerging AI technologies.
  • Collaborate with AI engineering teams to operationalize models and integrate them into enterprise applications and workflows.
  • Develop analytical methodologies for risk detection, anomaly identification, behavioral analysis, and decision intelligence.
  • Participate in AI experimentation, proof-of-concept development, pilot initiatives, and production deployments.

Data Engineering & Platform Collaboration

  • Architect the target-state Enterprise AI Security Platform, including platform components, security services, data flows, APIs, integration patterns, trust boundaries, and deployment models.
  • Partner with engineering teams to build scalable data pipelines and analytics workflows.
  • Work with enterprise datasets across SQL, NoSQL, cloud-native platforms, and distributed data environments.
  • Contribute to MLOps practices, reproducible workflows, version-controlled development, and model lifecycle management.
  • Support integration of machine learning solutions with APIs, cloud services, data platforms, and business applications.

Governance, Documentation & Responsible AI

  • Document models, assumptions, methodologies, testing procedures, and decision logic.
  • Maintain reproducible and auditable workflows to support governance, compliance, and operational excellence.
  • Ensure compliance with responsible AI principles, privacy requirements, cybersecurity standards, and ethical AI practices.
  • Contribute to model governance, validation frameworks, and risk management activities.

Cross-Functional Leadership

  • Collaborate with stakeholders, architects, engineers, UX teams, and business leaders to define analytical requirements and success metrics.
  • Present findings, recommendations, and technical concepts to both technical and non-technical audiences.
  • Mentor junior team members and contribute to the development of data science best practices and standards.
Requirements:


Required Experience and Skills

  • 5+ years of professional experience in data science, machine learning, advanced analytics, or applied AI.
  • Demonstrated experience developing and deploying predictive models and machine learning solutions in production environments.
  • Strong experience with statistical analysis, machine learning algorithms, and data modeling techniques.
  • Experience working with large-scale datasets and modern data platforms.
  • Strong programming skills in Python and modern data science frameworks.
  • Experience working in collaborative Agile or product-focused development environments.
  • Excellent communication, presentation, and problem-solving skills.
  • Ability to pass required background screening and obtain/maintain appropriate customer approvals or government clearance, where required.
  • Must be legally authorized to work in the United States without sponsorship now or in the future.

Preferred Qualifications

  • Experience with enterprise-scale AI, cloud-based analytics platforms, or advanced AI/ML ecosystems.
  • Familiarity with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and AI agent frameworks.
  • Experience supporting federal government, regulated, or highly governed environments.
  • Knowledge of AI governance, model risk management, privacy, security, and responsible AI frameworks.
  • Experience with MLOps, CI/CD pipelines, and model monitoring.


Technical Skills


Programming & Analytics

  • Python (Pandas, NumPy, Scikit-learn, TensorFlow and/or PyTorch)

Data & Engineering

  • SQL, NoSQL Databases, Apache Spark, Kafka, Cloud Data Platforms, API Integration

AI & Machine Learning

  • Predictive Modeling, Statistical Analysis, Simulation & Forecasting, M/L Lifecycle Management, Model Evaluation & Validation, Generative AI & LLM Concepts

Visualization

  • Plotly, Matplotlib, Seaborn

Development & Operations

  • Git/GitHub/GitLab, MLOps, CI/CD, Reproducible Workflows, Model Governance


Core Competencies

  • Advanced analytical and critical thinking skills
  • Strong business and technical problem-solving ability
  • Data-driven decision making
  • Cross-functional collaboration and stakeholder engagement
  • Communication of complex technical concepts to diverse audiences
  • Commitment to responsible and ethical AI practices
  • Continuous learning and innovation mindset
  • Strong attention to quality, accuracy, and documentation


Education and Certifications

  • Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field required. Master's degree in Data Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Computer Science, or related field preferred.
  • Professional certifications in Data Science, Machine Learning, AI, Cloud Platforms, or related technologies preferred.


Physical Requirements

  • Prolonged periods of sitting at a desk and working on a computer. May need to lift up to 25 pounds occasionally.


What Success Looks Like


Success in this role is measured by the delivery of scalable AI and analytics solutions that drive measurable business outcomes, improve operational efficiency, enhance decision-making capabilities, and establish trustworthy, well-governed machine learning practices across the organization. Candidates who thrive in this role are equally comfortable exploring data, building sophisticated models, partnering with stakeholders, and ensuring solutions are production-ready, secure, and impactful.



Who We Are


Tanaq Technical Services (TTS) strives to deeply understand and analyze our clients’ vision, needs, and requirements so we may provide alternative solutions, empowering them to choose the best resolution. We aim to achieve excellence by delivering on our commitments to our clients, employees, and partners.


Our Commitment to Non-Discrimination


Tanaq Technical Services is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, or local law. Tanaq complies with the Drug-free Workplace Act of 1988 and E-Verify.


If you are an individual with a disability and need assistance completing any part of the application process, please email accommodation@tanaq.com to request a reasonable accommodation. This email is for accommodation requests only and cannot be used to inquire about the status of applications.


Notice on Candidate AI Usage


Tanaq is committed to ensuring a fair and competitive interview process for all candidates based on their experience, skills and education. To ensure the integrity of the interview process, the use of artificial intelligence (AI) tools to generate or assist with responses during phone, in person and virtual interviews is not allowed. However, candidates who require a reasonable accommodation that may involve AI are required to contact us prior to their interview at accommodation@tanaq.com.


To apply for this position, visit:

https://recruiting.paylocity.com/Recruiting/Jobs/Details/4423049

Apply