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Data Analytics Professional Jobs in Alaska (NOW HIRING)

GCI

Data Analytics Engineer I (Future Opening)

Anchorage, AK · On-site

$118K - $142K/yr

GCI's Data Analytics Engineer I will be responsible for designing, developing, and maintaining ... Provide a professional level of service to both external and internal customers. * RELIABILITY ...

Pacs

$100/hr

Stay current with best practices in data engineering, analytics, and the Microsoft Fabric ecosystem ... Our Employee Assistance Plan (EAP) provides confidential support for personal and professional ...

Northrim Bank

Data Architect

Anchorage, AK · On-site

$4.2K/wk

... analysts, auditors, and executives * You don't just build data platforms you design data trust Work Environment * Professional office setting with a moderate noise level * Collaborative, cross ...

Thread

Professional Development Manager

Anchorage, AK · On-site

Oversee and support statewide team communication, strategic planning, data analysis, and ... The specific work a Professional Development Manager could oversee and/or conduct includes, but is ...

Data Annotation

$50 - $60/hr

We're seeking experienced finance professionals with advanced degrees (MBA+) and professional ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

ProSidian Consulting

... professionals to complete a wide range of engagements for public and private, defense and civilian ... Bachelor's in Engineering, Data Analytics, Business, or Environmental Science; 5-8 years experience;

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All JobsData Analytics Professional JobsData Analytics Professional Jobs in Alaska

Data Analytics Professional information

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How much do data analytics professional jobs pay per hour?

As of Jun 28, 2026, the average hourly pay for data analytics professional in Alaska is $58.96, according to ZipRecruiter salary data. Most workers in this role earn between $47.36 and $66.78 per hour, depending on experience, location, and employer.

What is the highest paying job in data analytics?

The highest paying roles in data analytics are often senior positions such as Data Analytics Director, Chief Data Officer, or Data Science Manager, which require extensive experience, advanced skills in programming, machine learning, and data strategy. These roles typically offer six-figure salaries and may include leadership responsibilities and specialized certifications.

What do data analytics professionals do?

Data analytics professionals analyze large datasets to identify trends, patterns, and insights that support business decision-making. They use tools like Excel, SQL, and data visualization software, and often work with stakeholders to interpret data and recommend actions. Strong analytical skills and knowledge of statistical methods are essential in this role.

What is the difference between Data Analytics Professional vs Data Analyst?

AspectData Analytics ProfessionalData Analyst
CredentialsOften requires a degree in data science, statistics, or related fields; certifications like CAP, Google Data AnalyticsTypically holds a degree in similar fields; certifications are common but not mandatory
Work EnvironmentWorks across various industries, often in teams, handling complex data projectsFocuses on data collection, cleaning, and basic analysis, often in business settings
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firmsCommon in retail, marketing, finance, and healthcare sectors

While both roles involve analyzing data, Data Analytics Professionals often handle more complex projects and require broader skill sets, including advanced analytics and data modeling. Data Analysts typically focus on data preparation and basic analysis to support decision-making. Both roles are essential in data-driven organizations, but the scope and complexity of tasks differ.

Is AI replacing data analysts?

AI tools are automating certain data analysis tasks, but the role of a data analytics professional involves interpreting complex data, developing insights, and making strategic recommendations that AI cannot fully replicate. Data analysts with skills in programming, statistical methods, and data visualization remain essential for translating data into actionable business decisions.

Is 40 too late for data science?

Data analytics professionals can successfully transition into data science at any age, including 40, as the field values skills such as programming, statistical analysis, and domain knowledge. Many individuals acquire relevant certifications or learn tools like Python, R, and SQL later in their careers to enhance their qualifications.
What are the most commonly searched types of Data Analytics jobs in Alaska? The most popular types of Data Analytics jobs in Alaska are:
What cities in Alaska are hiring for Data Analytics Professional jobs? Cities in Alaska with the most Data Analytics Professional job openings:
Data Analytics Professional jobs near you
Data Analytics Engineer I (Future Opening)

Data Analytics Engineer I (Future Opening)

GCI

Anchorage, AK • On-site

$67K - $112K/yr

Full-time

Posted 9 days ago

Job description


This posting is to gather interest for the Data Analytics Engineer I. We are not currently hiring, but will be contacting candidates when we have an opening.
GCI's Data Analytics Engineer I will be responsible for designing, developing, and maintaining interactive dashboards and reports that support data driven decision making within the organization. This hybrid role combines the functions of data engineering and analytics engineering, enabling the organization to leverage large-scale data for actionable business insights. Position will collaborate with cross-functional teams to ensure the quality, efficiency, and scalability of data while providing advanced analytics solutions to enhance network performance, customer experience, and operational efficiency.
ESSENTIAL DUTIES AND RESPONSIBILITIES AT ALL LEVELS:
Analytics Engineering:
  • Develop and implement data models, algorithms, and analytical solutions to derive insights from large datasets, including network performance analysis, customer behavior modeling, churn prediction, and operational optimization.
  • Implement AI driven workflows against data within analytical projects. Create automated reporting and visualization tools (e.g., dashboards, KPI reports) to communicate insights to stakeholders and drive data-informed decision-making.
  • Collaborate with business units to understand analytical needs and translate them into actionable data solutions.

Data Engineering:
  • Design, develop, and maintain robust data pipelines that efficiently collect, process, and transform data from various telecommunications sources (e.g., network performance, customer usage data, call data records, billing systems).
  • Implement and manage ETL (Extract, Transform, Load) processes to ensure seamless integration of data from multiple systems into a centralized data warehouse or data lake.
  • Ensure data quality and integrity by identifying, resolving, and preventing data discrepancies and errors.
  • Optimize and streamline data storage and retrieval processes to support real-time and batch data analysis needs.

Cross-Functional Collaboration:
  • Work closely with data scientists, business analysts, and IT teams to design and implement visualizations that provide meaningful insights.
  • Provide technical guidance and support to junior team members and other departments in data-related initiatives.

Continuous Improvement & Innovation:
  • Stay up to date with the latest trends and technologies in data engineering, analytics, and telecommunications.
  • Identify opportunities to improve existing data systems, pipelines, and analytics models to drive greater efficiency and business impact.
  • Contribute to the development and adoption of new data technologies, methodologies, and best practices within the organization.
COMPETENCIES:
  • ACCOUNTABILITY- Takes ownership for actions, decisions, and results; openly accepts feedback and demonstrates a willingness to improve.
    • Take ownership and accountability of problems and facilitate finding a solution, involving other groups as necessary.
    • Own and manage priorities and individual tasks without direct supervision.
    • Take the initiative and seek out opportunities. Assess and accept risks and learn from mistakes.
  • BASIC PRINCIPLES - Interacts with people in a way that builds mutual trust, confidence, and respect; adheres to GCI's Code of Conduct for Employees - the Basic Principles.
    • Lead by example on all fronts.
    • Guide development teams in a manner that creates success and allows for future self-sufficiency.
  • Foster innovation and promote teamwork.
  • COLLABORATION - Works effectively with others to accomplish common goals and objectives; maintains positive relationships even under difficult circumstances.
    • Build and maintain effective working relationships with leadership, peers, customers, and vendors. Work to resolve problem relationships directly.
  • COMMUNICATION- Conveys thoughts and expresses ideas appropriately and professionally.
    • Build and maintain effective working relationships with leadership, peers, customers, and vendors.
    • Work to resolve problem relationships directly.
    • Create clear and concise written documentation for a variety of audiences, including developers, business analysts and business users.
  • COMPLIANCE - Follows internal controls; protects company and customer confidential information; abides by GCI's Code of Business Conduct & Ethics.
  • Reviews modules for quality assurance.
  • CUSTOMER FOCUS - Demonstrates commitment to service excellence; gives high priority to customer satisfaction.
    • Provide a professional level of service to both external and internal customers.
  • RELIABILITY - Consistently follows through on assigned tasks as expected; demonstrates timely attendance at meetings, training, and other work obligations.
  • RESULTS - Uses a combination of knowledge, initiative, sound decision making, innovation, adaptability, and problem solving.
  • SAFETY & SECURITY - Supports a safe work environment by following all workplace safety rules and guidelines; complies with applicable Security policies and procedures.
  • TECHNICAL COMPETENCIES -
    • MS Office knowledge (e.g., Outlook, Teams, Word, Excel). Ability to Design, Evaluate, and test data infrastructure.
    • Proficiency in SQL, Python, and R for data manipulation and analytics.
    • Experience with big data technologies (e.g., Spark, Databricks) and cloud platforms (AWS, Azure, Google Cloud).

Proficient with data visualization tools (e.g., Tableau, Power BI).
  • Knowledge of machine learning algorithms and statistical analysis techniques.
  • Familiarity with telecommunications systems and related data types (e.g., network performance metrics, call data records).

Additional Job Requirements:
Works under moderate supervision, supports the team with reasonably complex issues, processes and projects developing a stronger working knowledge of subject matter.
  • Assist in the collection, processing, and cleaning of raw data from various sources (e.g., network performance, customer usage data, billing systems).
  • Develop and maintain dashboards and reports.
  • Write basic SQL queries to query and extract data for analysis.
  • Assist senior team members with data preparation tasks, including data validation and transformation.
  • Conduct basic exploratory data analysis (EDA) and assist in visualizing data for team reports.
  • Document data processes and workflows to maintain clarity on pipeline structures and operational processes.

Additional Competencies:
  • Familiarity with SQL, Python, and data visualization tools (e.g., Tableau, Power BI).
  • Ability to collaborate with cross-functional teams.
  • Eagerness to learn and develop technical skills in data engineering and analytics.
  • Basic understanding with ETL processes, data pipeline design, and data warehousing.
  • Basic understanding of telecommunications systems, data, network architecture, and key performance metrics.
  • Familiarity with spatial data analysis.

Minimum Qualifications:
Required: *A combination of relevant work experience and/or education sufficient to perform the duties of the job may substitute to meet the total years required on a year-for-year basis
  • High School diploma or equivalent.
  • Bachelor's degree in Computer Science, Data Science, Engineering, Telecommunications, or a related field. *
  • Minimum of one (1) year of experience in data engineering, analytics engineering, or a related role in the telecommunications industry. *

Preferred:
  • Advanced degree (Master's or PhD) in Data Science, Machine Learning, or a related field.
  • Familiarity with network optimization, customer experience analysis, or predictive analytics in telecommunications.
  • Other telecom industry or job specific certifications.

DRIVING REQUIREMENTS:
This position may require access to reliable transportation for occasional travel, such as between retail store locations, offices, worksites, or other locations as needed.
PHYSICAL REQUIREMENTS and WORKING CONDITIONS:
  • Work is primarily sedentary, requiring daily routine computer usage.
  • Ability to work shifts as assigned, work in standard office/home office setting, and operate standard office equipment.
  • Ability to accurately communicate information and ideas to others effectively.
  • Physical agility and effort sufficiently to perform job duties safely and effectively.
  • Ability to make valid judgments and decisions.
  • Available to work additional time on weekends, holidays, before or after normal work hours when necessary.
  • Must work well in a team environment and be able to work with a diverse group of people and customers.
  • Virtual workers must comply with remote work policies and agreements.
The company and its subsidiaries operate in a 24/7 environment providing critical services to Alaskans and may need to respond to public health and safety matters or other business emergencies. Due to business needs employees may be contacted outside of the core business hours to respond to an immediate emergency. As such, you will be requested to provide emergency after hours contact numbers, to include your home and cell phone numbers if you have those services. Culture, Engagement, and Connection: At GCI, we foster an environment where the unique perspectives of our employees, customers, and fellow Alaskans are celebrated. We add value to our community by nurturing and empowering each member of our workforce, ensuring equal opportunities for every Trailblazer. EEO: GCI is an equal opportunity employer. Qualified applicants are considered for employment without regard to race, color, religion, national origin, age, sex, sexual orientation, gender identity, marital status, mental or physical disability, veteran status, or any other status or classification protected under applicable state or federal law. DISCLAIMER: The above information in this description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job. All employees of GCI work in support of the GCI Mission Statement and Declaration of Principles which are located on the GCI Career page and Employee portal.

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