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Remote Data Analyst Jobs in Buffalo, MN (NOW HIRING)

This is a remote-first role with occasional (~1x month) travel. Responsibilities and Duties ... Analyze claims and cost savings data to drive insights for reporting and product improvement

This is a remote-first role with occasional (~1x month) travel. Responsibilities and Duties ... Analyze claims and cost savings data to drive insights for reporting and product improvement

You will assist with sales data analysis, contract renewal engagement, revenue retention support ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Analyze key performance indicators and interpret historical data systems' performance to identify, recommend, and implement design changes and modifications that reduce life-cycle costs, improve ...

... reviewing applications, analyzing resumes, or assessing responses and identifying potential ... If you would like more information about how your data is processed, please contact us. apply for ...

Showing results 21-40

Remote Data Analyst information

See Buffalo, MN salary details

$35.8K

$87K

$143.2K

How much do remote data analyst jobs pay per year?

As of Sep 4, 2026, the average yearly pay for remote data analyst in Buffalo, MN is $87,003.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,800.00 and $102,100.00 per year, depending on experience, location, and employer.

What does a remote data analyst do?

A Remote Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed business decisions, all while working from a location outside of a traditional office. They use statistical tools and software to interpret complex datasets, identify trends, and generate reports. Remote Data Analysts collaborate with team members via digital communication platforms and often present their findings to stakeholders to guide strategy and operations. Their work is essential in industries such as finance, healthcare, marketing, and technology, where data-driven decisions are crucial.

What does a remote data analyst do?

Remote data analysts use a range of methods to chart, examine, and analyze data for their clients. Unlike in-house data analysts, remote data analysts, work from home or a different location outside of the office. As a remote data analyst, your job is to evaluate a company’s data using a combination of mathematical inspection, transformation, and modeling techniques to simplify and condense it. Once the analysis is complete, you create reports for management to use to make critical decisions; this is why remote data analysts need to confirm the accuracy of the data. You may also need to present your reports to stakeholders.

What are the key skills and qualifications needed to thrive as a remote data analyst?

To thrive as a Remote Data Analyst, you need strong analytical skills, proficiency in statistics, and a degree in a quantitative field such as mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Excel, Python or R, and visualization platforms such as Tableau or Power BI is typically required. Excellent communication, self-motivation, and time management are crucial soft skills for collaborating remotely and presenting insights effectively. These skills ensure accurate data-driven decision-making and effective remote teamwork in a digital work environment.

How do remote data analysts typically collaborate with team members and stakeholders given the virtual work environment?

Remote Data Analysts often rely on digital communication tools such as Slack, Microsoft Teams, and Zoom to stay connected with colleagues and stakeholders. They participate in regular virtual meetings, share dashboards or reports via cloud-based platforms, and provide data-driven insights to support decision-making. Successful remote analysts proactively communicate their findings, clarify requirements, and coordinate with cross-functional teams such as IT, marketing, or finance to ensure alignment on project goals and deliverables.

What is the difference between Remote Data Analyst vs Remote Data Scientist?

AspectRemote Data AnalystRemote Data Scientist
Required CredentialsBachelor's in Data, Statistics, or related field; often certifications in Excel, SQL, or TableauBachelor's or Master's in Data Science, Computer Science, or related; certifications in Python, R, machine learning
Work EnvironmentPrimarily office-based or remote, focusing on data analysis and reportingPrimarily remote, involving complex data modeling and predictive analytics
Employer & Industry UsageUsed across finance, marketing, healthcare, and retail sectorsCommon in tech, finance, and research industries

Remote Data Analysts focus on interpreting data, creating reports, and supporting decision-making, while Remote Data Scientists develop models, perform advanced analytics, and work on predictive insights. Both roles require strong analytical skills, but Data Scientists typically have more technical expertise in programming and machine learning.

Are remote data analyst jobs still in demand?

Remote data analyst jobs remain in high demand due to the increasing reliance on data-driven decision making across industries. Skills in data visualization, SQL, and statistical analysis are particularly valuable, and many companies continue to expand their remote analytics teams to access a broader talent pool.

Can I get remote jobs as a remote data analyst?

Remote data analyst positions are widely available and often require skills in data analysis tools like Excel, SQL, and Python. Many companies offer remote roles with flexible schedules, and candidates typically need a strong analytical background and good communication skills.

Can you work remotely as a remote data analyst?

Remote data analysts can often work from home or other locations, depending on the employer’s policies. Many companies offer remote positions that require skills in data analysis tools like Excel, SQL, or Python, and a reliable internet connection. Availability of remote work varies by organization and role requirements.

What are the most commonly searched types of Data Analyst jobs in Buffalo, MN?

The most popular types of Data Analyst jobs in Buffalo, MN are:

What job categories do people searching Remote Data Analyst jobs in Buffalo, MN look for?

The top searched job categories for Remote Data Analyst jobs in Buffalo, MN are:

What cities near Buffalo, MN are hiring for Remote Data Analyst jobs?

Cities near Buffalo, MN with the most Remote Data Analyst job openings:

Infographic showing various Remote Data Analyst job openings in Buffalo, MN as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 20% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $87,003 per year, or $41.8 per hour.

Director, AI Data Strategy and Enablement - Remote

UnitedHealth Group

Minnetonka, MN • On-site, Remote

Full-time

Retirement

Posted 3 days ago

New


UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

191st of 898 rated healthcare providers


Job description

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
UnitedHealth Group is building an enterprise-scale AI operating model. AI experiences require trusted, connected, contextual, interpretable, governed, and actionable data that AI systems can discover, reason over, and use appropriately across journeys and workflows. In a complex health care enterprise, this data is distributed across products, platforms, business units, legacy systems, documents, operational processes, and external partners.
As Director, AI Data Strategy & Enablement, you will define and lead the strategy for how enterprise data, context, and capabilities enable next-generation digital and AI experiences for our 50+ million members. You will establish the vision, operating model, priorities, standards, and roadmap required to make enterprise data AI-ready and agent-ready.
This is a highly strategic, cross-functional leadership role. You will work across Digital, Product, Technology, Data & Analytics, AI, Architecture, Operations, Compliance, Risk, and business teams to identify high-value opportunities, lead structured discovery, define future-state capabilities, and mobilize a highly matrixed organization around a common strategy.
You will bring design thinking, systems thinking, structured discovery, and data strategy to ambiguous enterprise problems, translating business and experience needs into actionable data and capability strategies. You will also shape how data and context are made usable by AI agents and digital skills, including discoverability, semantics, retrieval, permissions, interoperability, governance, and observability.
You will help move the organization from fragmented sources of information toward a trusted, reusable, semantic, interoperable data ecosystem that enables personalized digital experiences and scales AI safely across the enterprise.
You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.
Primary Responsibilities:
  • Define Enterprise AI Data Strategy & Roadmap
    • Define the vision, principles, strategic priorities, and multi-year roadmap for AI-ready and agent-ready data aligned to enterprise AI and digital experience priorities
    • Identify the data, semantic, knowledge, context, access, interoperability, governance, and observability capabilities required to scale AI
    • Prioritize investments based on member and business value, feasibility, reuse potential, and strategic importance
    • Balance near-term AI use cases with foundational capabilities that enable long-term scale and reduce fragmented or duplicative investments
    • Establish the operating model, decision rights, and partnerships needed to execute the strategy across the enterprise
  • Lead Discovery, Experience Strategy & Enterprise Alignment
    • Lead structured discovery with product, business, clinical, operations, technology, data, and experience stakeholders to understand needs, outcomes, constraints, and root causes
    • Apply design thinking, journey-based discovery, systems thinking, and hypothesis-driven problem solving to identify opportunities for AI-enabled experiences
    • Translate ambiguous problems into clear strategic choices, capability requirements, and actionable roadmaps
    • Facilitate alignment across stakeholders with competing priorities, different definitions, or conflicting perspectives on data and technology
    • Build executive alignment and influence decisions across a complex, highly matrixed organization without direct authority
  • Shape the Data Foundation for Agentic AI
    • Define principles and requirements for agent-ready data, including trust, freshness, lineage, semantics, discoverability, permissions, interoperability, and machine usability
    • Shape the role of semantic models, metadata, ontologies, knowledge, data products, retrieval, and context layers in AI experiences
    • Partner with Architecture, Technology, Engineering, and Data leaders to establish scalable patterns for AI access to enterprise data and systems, including APIs, tools, retrieval services, and other governed access mechanisms
    • Ensure AI experiences are grounded in authoritative enterprise sources and business context and can operate within appropriate policy, risk, and human-escalation controls
    • Establish requirements for data provenance, observability, traceability, auditability, and responsible use as AI systems retrieve information, make recommendations, or take action
  • Drive Enterprise Standards, Change & Measurable Outcomes
    • Establish standards for data domains, business definitions, semantic models, metadata, schemas, APIs, and reusable data products to improve interoperability and consistency
    • Partner with enterprise architecture and technology leaders to influence future-state architecture and promote reusable enterprise capabilities
    • Lead organizational change required to adopt new data strategies, standards, operating models, and ways of working across a complex matrix
    • Create executive narratives and business cases that connect data strategy to member experience, business value, productivity, risk reduction, and enterprise transformation
    • Define and track measures of AI data readiness, reuse, quality, adoption, time-to-value, and business impact; use results and learnings to continuously refine the strategy

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
Required Qualifications:
  • 8+ years of progressive experience in data strategy, product strategy, digital transformation, technology strategy, AI enablement, analytics, or a related field
  • Proven experience leading structured discovery and strategic problem solving and translating ambiguous business or customer problems into actionable opportunities and roadmaps
  • Demonstrated experience defining and executing enterprise-level data or AI strategies in complex organizations
  • Solid understanding of modern enterprise data concepts, including data products, metadata, data quality, lineage, interoperability, APIs, semantic modeling, and governed data access
  • Solid understanding of GenAI and agentic AI, including how AI agents access data, retrieve context, use tools, interact with enterprise systems, and operate within governance constraints
  • Demonstrated ability to use design thinking, systems thinking, journey mapping, or comparable structured problem-solving approaches
  • Demonstrated success leading change and influencing senior stakeholders across a complex, matrixed organization without direct authority
  • Proven excellent executive communication, facilitation, strategic planning, and storytelling skills, with the ability to translate technical concepts into business decisions and measurable outcomes

Preferred Qualifications:
  • Experience in healthcare, health insurance, financial services, or another highly regulated industry
  • Experience building or scaling an AI-ready or agent-ready data strategy
  • Experience with semantic layers, ontologies, knowledge graphs, enterprise metadata, data catalogs, retrieval architectures, or reusable data products
  • Experience supporting LLMs, RAG, AI assistants, copilots, or agentic workflows
  • Experience establishing enterprise operating models, governance structures, standards, or Centers of Excellence
  • Familiarity with modern cloud data platforms and architectures such as Azure, AWS, GCP, Databricks, Snowflake, or comparable technologies
  • Familiarity with emerging agent interaction and tool-access patterns such as MCP or comparable enterprise integration approaches

*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $134,600 - $230,800 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.
UnitedHealth Group is a drug-free workplace. Candidates are required to pass a drug test before beginning employment.

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