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Data Scientist Jobs in Alaska (NOW HIRING)

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Data Scientist information

See Alaska salary details

$40.4K

$132.2K

$211.6K

How much do data scientist jobs pay per year?

As of Aug 4, 2026, the average yearly pay for data scientist in Alaska is $132,182.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,100.00 and $146,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks, data visualization tools, and big data platforms like TensorFlow, Tableau, and Hadoop, as well as certifications in data science, are highly valued. Excellent problem-solving skills, curiosity, and the ability to communicate complex findings clearly set outstanding data scientists apart. These skills and qualities are crucial for extracting actionable insights from data, driving business decisions, and collaborating effectively with stakeholders.

What do data scientists do?

Data scientists collect, confirm, and interpret data to determine useful information for their employer. They help organizations identify patterns and trends in their data to provide information about lucrative opportunities, necessary improvements, and potential innovations. The information data scientists get from the records they gather helps businesses make major decisions in critical areas, such as product development, sales and marketing techniques, and client retention. Data scientists are highly educated; the majority of them have at least a master's degrees, and many have doctorates. Data scientists are valuable members of organizations in many different industries, including pharmaceuticals, manufacturing, and banking.

Is a data scientist job still in demand?

Yes, data scientist roles remain in high demand across various industries due to the increasing reliance on data-driven decision making. Skills in machine learning, statistical analysis, and programming languages like Python or R are highly valued, and employment opportunities continue to grow as organizations seek to leverage big data for competitive advantage.

Is data science a math heavy field?

Data scientists rely heavily on mathematics, including statistics, linear algebra, and calculus, to analyze data and develop models. Strong math skills are essential for tasks like machine learning, data analysis, and algorithm development, often complemented by programming in languages such as Python or R. However, practical skills in data manipulation and domain knowledge are also important for success in the field.

What is the difference between Data Scientist vs Data Analyst?

AspectData Scientist
Required CredentialsDegree in Computer Science, Statistics, or related field; often requires advanced degrees
Work EnvironmentResearch and development, predictive modeling, machine learning projects
Employer & Industry UsageTech companies, finance, healthcare, consulting firms
Common Search & ComparisonOften compared due to overlapping skills in data analysis and modeling

Data Scientists focus on building predictive models, advanced analytics, and machine learning, often requiring higher-level technical skills and education. Data Analysts primarily interpret existing data, generate reports, and support decision-making with descriptive analytics. While both roles analyze data, Data Scientists handle complex modeling and predictive tasks, whereas Data Analysts focus on data interpretation and reporting.

What are some typical projects data scientists work on, and how do they collaborate with other teams?

Data Scientists often work on projects such as building predictive models, analyzing large datasets to uncover trends, and developing data-driven solutions to business problems. They regularly collaborate with cross-functional teams, including software engineers, data engineers, and business analysts, to ensure that their insights are actionable and aligned with business goals. Effective communication and teamwork are essential, as Data Scientists frequently need to present complex findings to non-technical stakeholders and incorporate feedback from various departments.
More about Data Scientist jobs
What are the most commonly searched types of Data Scientist jobs in Alaska? The most popular types of Data Scientist jobs in Alaska are:
What are popular job titles related to Data Scientist jobs in Alaska? For Data Scientist jobs in Alaska, the most frequently searched job titles are:
What job categories do people searching Data Scientist jobs in Alaska look for? The top searched job categories for Data Scientist jobs in Alaska are:
What cities in Alaska are hiring for Data Scientist jobs? Cities in Alaska with the most Data Scientist job openings:
What are popular job titles related to Data Scientist jobs in AK? For Data Scientist jobs in AK, the most frequently searched job titles are:
Data Scientist jobs near you
Infographic showing various Data Scientist job openings in Alaska as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $132,182 per year, or $63.5 per hour.

Principal Data Scientist

Sedgwick

Minto, AK • On-site, Remote

Other

Re-posted 26 days ago

Sedgwick rating

7.6

Company rating: 7.6 out of 10

Based on 319 frontline employees who took The Breakroom Quiz

207th of 301 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

JobResponsibilities

  • Leadthedesignanddevelopmentofadvancedstatisticalandmachinelearningmodelsthatimproveclaimsoutcomes,operationalefficiency,andriskmanagement.
  • Serveasthetechnicalauthorityforcomplexmodelinginitiativesincludingfrauddetection,claimsseverityprediction,litigationriskmodeling,andrecoveryoptimization.
  • Developpredictiveandprescriptivemodelsusingstructuredandunstructuredclaimsdata,includingadjusternotes,medicalrecords,andpolicydocumentation.
  • Architectmodelingapproachesthatleveragemoderntechniquessuchasgradientboosting,deeplearning,NLP,anomalydetection,andprobabilisticmodeling.
  • PartnerwithAIEngineeringteamstoproductionizemodelsandintegratethemintoenterpriseAIplatformsandoperationalsystems.
  • Designfeatureengineeringstrategiesandmodelingpipelinesusinglarge-scaleenterprisedatasets.
  • Establishbestpracticesformodeldevelopment,experimentation,validation,andreproducibility.
  • Leadadvancedanalyticaltechniquessuchascausalinference,scenariosimulation,andriskscoringmethodologies.
  • Buildandmaintainmodelevaluationframeworksthatmeasureaccuracy,bias,stability,andbusinessimpact.
  • Monitordeployedmodelsfordrift,degradation,andchangingdatadistributions,andrecommendrecalibrationstrategies.
  • Providetechnicalguidancetodatascientistsandanalystsacrosstheorganization.
  • Mentorjuniorteammembersonstatisticalmethods,machinelearningtechniques,andanalyticalrigor.
  • Translatecomplexanalyticalfindingsintoclear,actionableinsightsforbusinessleadersandoperationalteams.
  • CollaboratewithClaimsOperations,Finance,Risk,andITstakeholderstoidentifyhigh-impactanalyticalopportunities.
  • Evaluateexternaldatasourcesandthird-partyanalyticalsolutionsthatenhancepredictivecapabilities.
  • Ensureanalyticalmethodologiesalignwithenterprisegovernancestandardsandregulatoryexpectations.
  • ContributetoSedgwick'sbroaderAIandadvancedanalyticsstrategybyidentifyingemergingtechnologiesandmodelingapproaches.
  • LeadresearchandinnovationinitiativesthatadvanceSedgwick'spredictiveanalyticscapabilities.

Qualifications

  • Master'sorPhDinDataScience,Statistics,Mathematics,ComputerScience,Economics,orrelatedquantitativediscipline.
  • 8-12+yearsofexperienceindatascience,statisticalmodeling,oradvancedanalyticsroles.
  • Deepexpertiseinmachinelearningalgorithms,statisticalmodelingtechniques,andpredictiveanalyticsmethodologies.
  • StrongprogrammingskillsinPython,R,orsimilaranalyticallanguages.
  • Extensiveexperienceworkingwithlarge,complexdatasetsinenterpriseenvironments.
  • Provenexperiencedesigningandimplementingend-to-endmodelingpipelines.
  • Strongunderstandingofmodelvalidation,featureengineering,andperformanceevaluationtechniques.
  • Experiencecollaboratingwithengineeringteamstodeploymodelsintoproductionsystems.
  • Familiaritywithdistributeddataprocessingtoolsandmoderndataplatformspreferred.
  • Experienceininsurance,claimsmanagement,healthcare,orfinancialservicesanalyticspreferred.
  • Abilitytocommunicateadvancedanalyticalconceptstobothtechnicalandnon-technicalstakeholders.
  • Demonstratedabilitytoleadcomplexanalyticalinitiativesthatdrivemeasurablebusinessvalue.
  • Strongmentoringandtechnicalleadershipcapabilities.

#LI-TS1 #remote

Sedgwickis 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.

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