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Analytics Manager Jobs in Alaska (NOW HIRING)

Gather, interpret, analyze and, correlate large amounts of narrative and statistical information ... Provide direction to Directorate managers in the preparation of SF-52 packages. * Serve as the ...

Gather, interpret, analyze and, correlate large amounts of narrative and statistical information ... Provide direction to Directorate managers in the preparation of SF-52 packages. * Serve as the ...

Gather, interpret, analyze and, correlate large amounts of narrative and statistical information ... Provide direction to Directorate managers in the preparation of SF-52 packages. * Serve as the ...

Gather, interpret, analyze and, correlate large amounts of narrative and statistical information ... Provide direction to Directorate managers in the preparation of SF-52 packages. * Serve as the ...

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Analytics Manager information

See Alaska salary details

$69.5K

$135K

$192.8K

How much do analytics manager jobs pay per year?

As of Aug 9, 2026, the average yearly pay for analytics manager in Alaska is $134,969.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,700.00 and $160,500.00 per year, depending on experience, location, and employer.

What is an analytics manager?

An analytics manager translates raw data into insights that a business can use. Usually leading a team of analysts, your job duties include developing data analysis strategies, tracking and reporting on performance, implementing tools and solutions, and overseeing all analytics operations. You must stay up-to-date on current industry trends. Strong communication and analytical skills are required. Other qualifications include a bachelor’s degree in statistics, data management, or information technology and proven career experience in market research, statistical modelings, or project management.

Is data analytics a high paying job?

Data analytics roles, including Analytics Managers, tend to offer high salaries compared to many other positions, especially with experience and advanced skills in tools like SQL, Python, or Tableau. Compensation varies by industry, location, and company size, but generally, analytics managers earn above average salaries in the job market.

What is the difference between Analytics Manager vs Data Analyst?

AspectAnalytics ManagerData Analyst
Required CredentialsBachelor's or Master’s in Business, Analytics, or related fields; often certifications in analytics toolsBachelor's degree in Statistics, Mathematics, or related fields; certifications in data analysis tools
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersPerforms data cleaning, analysis, and reporting; works under supervision
Employer & Industry UsageUsed in corporate, finance, marketing, and tech sectors for strategic decision-makingCommon in research, finance, healthcare, and marketing for data insights

While both roles involve working with data, the Analytics Manager oversees teams and strategic projects, whereas Data Analysts focus on data collection, analysis, and reporting. The Analytics Manager typically has more leadership responsibilities and a broader scope.

How does an analytics manager typically collaborate with cross-functional teams to drive business insights?

Analytics Managers frequently work alongside teams such as marketing, product development, finance, and operations to translate data into actionable business strategies. They facilitate meetings to understand stakeholder goals, guide data collection efforts, and present findings in a way that's accessible to non-technical audiences. This cross-functional collaboration ensures that insights are aligned with business objectives and that projects are implemented effectively. Strong communication and project management skills are essential for success in this collaborative environment.

What are the key skills and qualifications needed to thrive as an analytics manager, and why are they important?

To thrive as an Analytics Manager, you need strong analytical skills, data interpretation expertise, leadership experience, and typically a degree in statistics, mathematics, computer science, or a related field. Familiarity with analytics platforms (such as Tableau, Power BI), programming languages (like SQL, Python, or R), and data management systems is essential, along with relevant certifications such as Google Analytics or Certified Analytics Professional (CAP). Excellent communication, problem-solving, and stakeholder management skills help you translate complex data insights into actionable business strategies. These competencies ensure data-driven decision-making, effective team leadership, and impactful business outcomes.

How much do analytics managers make in the US?

Analytics managers in the US typically earn a median salary of around $100,000 to $130,000 per year, depending on experience, industry, and location. Senior roles or those with specialized skills in data tools and leadership may earn higher compensation, often exceeding $150,000 annually.
What are the most commonly searched types of Analytics jobs in Alaska? The most popular types of Analytics jobs in Alaska are:
What are popular job titles related to Analytics Manager jobs in Alaska? For Analytics Manager jobs in Alaska, the most frequently searched job titles are:
What job categories do people searching Analytics Manager jobs in Alaska look for? The top searched job categories for Analytics Manager jobs in Alaska are:
What cities in Alaska are hiring for Analytics Manager jobs? Cities in Alaska with the most Analytics Manager job openings:
Infographic showing various Analytics Manager job openings in Alaska as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $134,969 per year, or $64.9 per hour.

Manager, People Analytics & Insights

6AM City

False Pass, AK • On-site

Full-time

Posted 2 days ago

New


Job description

Overview The Manager, People Analytics & Insights leads the development and delivery of data-driven insights that inform workforce strategy and elevate organizational performance. This role sits at the intersection of HR, business strategy, and data analytics, transforming complex data into clear, actionable recommendations for senior leadership. Reporting to the Director of People Analytics & Insights, the role works with senior HR leaders, COE heads, and business stakeholders to lead complex, often ambiguous analytical workstreams where the method, framing, and recommendation are as important as the data itself. Core Responsibilities Domain Ownership: Sets the analytical agenda of Talent Acquisition and Talent Development, defining relevant metrics, and ensuring outputs are consistently high quality, strategically relevant, and aligned to organizational priorities. Complex & Ambiguous Analysis: Lead end-to-end analysis of complex problems, independently framing the question, selecting or developing the appropriate methodology, and delivering findings that meaningfully shift understanding or decision-making. Stakeholder Influence: Engage senior HR and business stakeholders not just to explain findings, but to shape how they think about problems, influencing approach and direction. Insight Narrative & Recommendations: Develop well-reasoned, evidence-based recommendations. Data Quality & Governance Standards: Take accountability for the integrity and governance of people data within the domain, driving resolution across systems and process owners and contributing to enterprise-wide data standards. Informal Leadership: Provide ongoing coaching and quality review for junior analysts, reviewing outputs, developing analytical capability, and raising team standards through day-to-day collaboration. Innovation & Continuous Improvement: Proactively identify where existing approaches, models, or processes are insufficient and develop new ones, building new analytical capabilities where gaps exist. Benchmarking & External Perspectives: Lead benchmarking and external research initiatives, interpreting comparative data in context and synthesizing external trends into actionable implications for the organization. Skills & Qualifications Essential Experience: 8-12 years of experience in data analytics, people analytics, or a closely related discipline, with demonstrated experience owning analytical domains and driving insight-led decisions at a senior level in complex organizations. Education: Degree-level qualification (or equivalent) in Data Analytics, Statistics, Economics, Organizational Psychology, Human Resources, or a related field. Postgraduate qualification or equivalent depth of practice is an advantage. Technical Depth: Expert proficiency in BI tools (e.g. Power BI, Tableau) and Excel; advanced SQL; strong working proficiency in Python or R, including applying statistical or predictive methods to workforce data. Actively uses AI tools to enhance the quality and efficiency of analytical work. Methodological Range: Able to design as well as apply analytical methods - including regression modelling, clustering, attrition prediction, or scenario modelling - and judge which approach is right for the problem, not just the tool at hand. Framework & Standards Design: Demonstrated ability to design metrics frameworks, define analytical standards, or build scalable reporting infrastructure that others can work to. HR Systems & Data Governance: Deep familiarity with HR data platforms (e.g. Workday, SAP SuccessFactors), data structures, and governance considerations, including multi-country and GDPR complexity. Influence & Communication: Proven ability to shape how senior stakeholders think, not just reporting findings, but persuading, reframing, and leading discussions with credibility and composure under challenge. Autonomy: Consistently works independently on ambiguous, high-stakes problems. Comfortable operating where the question is unclear, the data is imperfect, and the answer matters. Desired Advanced Analytics in a Workforce Context: Hands-on experience applying predictive or machine learning techniques to people data - attrition modelling, skills clustering, internal mobility analysis, or similar. Cross-Domain People Analytics: Experience spanning more than one analytics domain - e.g. engagement, succession planning, workforce planning, and DEI - with the ability to connect insights across them. Global & Multi-Jurisdictional Data: Experience managing and interpreting datasets across multiple geographies, including navigating data privacy constraints. Consulting or Embedded Advisory Experience: #J-18808-Ljbffr