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Junior Data Analyst Jobs in Rio Rancho, NM (NOW HIRING)

Junior Business Operations Specialist

Albuquerque, NM · On-site

$25.75 - $34.50/hr

The Jr. BOS helps ensure knowledge management and data analytics functions remain accurate, timely, and impactful. Jr Business Operations Specialist Responsibilities * Data Collection and Validation ...

Junior Business Operations Specialist

Albuquerque, NM · On-site

$25.75 - $34.50/hr

The Jr. BOS helps ensure knowledge management and data analytics functions remain accurate, timely, and impactful.Jr Business Operations Specialist ResponsibilitiesData Collection and Validation:o ...

Data Architect

Albuquerque, NM · On-site

$61.75 - $79.50/hr

As a Junior Data Architect, you'll work alongside engineers, analysts, and business stakeholders to design and maintain data structures that make complex data accessible, reliable, and meaningful.

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Junior Data Analyst information

See Rio Rancho, NM salary details

$32.5K

$74.6K

$119.9K

How much do junior data analyst jobs pay per year?

As of Sep 8, 2026, the average yearly pay for junior data analyst in Rio Rancho, NM is $74,639.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,600.00 and $76,700.00 per year, depending on experience, location, and employer.

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

A Junior Data Analyst needs a solid grounding in statistics, data interpretation, and familiarity with data management, usually supported by a bachelor’s degree in a quantitative field. Competence in Excel, SQL, and data visualization tools like Tableau or Power BI, as well as basic programming in Python or R, is often required. Attention to detail, problem-solving abilities, and strong communication skills help analysts effectively interpret data and present insights. These skills are crucial for accurately analyzing data, informing business decisions, and contributing value to teams and organizations.

What does a junior data analyst do?

Junior data analysts work with a team of data analysts to translate data for businesses or government agencies. Data analysts work in many industries, including finance, accounting, health care, pharmaceuticals, technology, and in government agencies. They use algorithms and other tools to help an organization understand different aspects of this data, such as costs, market research, or sales numbers, which will enable them to make better business decisions for the future. A junior data analyst is an entry-level position and will involve seeking and collecting relevant data, as well as documenting the information be processed. Job duties include gathering data, interpreting the statistics, writing reports, and designing charts and graphs.

What are some common challenges faced by junior data analysts when working with large datasets, and how can they effectively overcome them?

Junior Data Analysts often encounter challenges such as data inconsistency, missing values, and handling large volumes of information when working with big datasets. To address these issues, it's important to develop strong data cleaning and preprocessing skills, use efficient data analysis tools like SQL and Python, and regularly collaborate with more experienced team members for guidance. Additionally, documenting your data processing steps and validating results with stakeholders can help ensure accuracy and build confidence in your analyses.

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

AspectJunior Data AnalystData Scientist
Required CredentialsBachelor's degree in data-related fields; basic knowledge of SQL, Excel, and data visualization toolsBachelor's or master's degree in data science, statistics, or related fields; advanced programming and statistical skills
Work EnvironmentEntry-level position in data teams; supports data collection, cleaning, and reportingAdvanced role involving complex data modeling, machine learning, and predictive analytics
Employer & Industry UsageCommon in finance, marketing, healthcare, and retail sectorsTypically found in tech, finance, and research-intensive industries

The main difference between a Junior Data Analyst and a Data Scientist lies in their experience, skill level, and responsibilities. Junior Data Analysts focus on data cleaning, basic analysis, and reporting, while Data Scientists handle complex modeling, machine learning, and predictive analytics. Both roles are essential in data-driven organizations, but they require different skill sets and experience levels.

Is it worth becoming a junior data analyst in 2026?

A junior data analyst role remains valuable in 2026 as demand for data skills continues to grow across industries. Success typically requires proficiency in tools like Excel, SQL, and data visualization software, along with a foundational understanding of statistics. Entry-level positions can lead to advanced roles with experience and additional certifications.

What are the most commonly searched types of Data Analyst jobs in Rio Rancho, NM?

The most popular types of Data Analyst jobs in Rio Rancho, NM are:

What are popular job titles related to Junior Data Analyst jobs in Rio Rancho, NM?

For Junior Data Analyst jobs in Rio Rancho, NM, the most frequently searched job titles are:

What job categories do people searching Junior Data Analyst jobs in Rio Rancho, NM look for?

The top searched job categories for Junior Data Analyst jobs in Rio Rancho, NM are:

What cities near Rio Rancho, NM are hiring for Junior Data Analyst jobs?

Cities near Rio Rancho, NM with the most Junior Data Analyst job openings:

Infographic showing various Junior Data Analyst job openings in Rio Rancho, NM as of August 2026, with employment types broken down into 92% Full Time, and 8% Part Time. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $74,639 per year, or $35.9 per hour.

Principal Data Analyst - Albuquerque, NM (Hybrid)

RS21

Albuquerque, NM • On-site

$125 - $150/hr

Other

Posted 10 days ago


Key responsibilities

  • Lead the design and execution of complex analytical projects, including data integration, longitudinal analysis, geospatial analysis, and statistical modeling.

  • Translate high-stakes, ambiguous business questions into rigorous analytical frameworks and synthesize findings into executive-level narratives and visualizations.

  • Define and promote analytical standards, evaluate tools and technologies, and serve as the technical authority on analytical questions.


Job description

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.

Full Time Albuquerque, NM, US

Salary Range: $118,000.00 To $158,000.00 Annually

Position Summary

RS21 is seeking a Principal Data Analyst to serve as the organization's foremost authority on data analysis, analytical methods, and the translation of complex data into actionable intelligence for mission-driven clients. This is the highest individual contributor level within the Data Analytics job family, and it carries significant responsibility for shaping how RS21 approaches analysis, insight delivery, and data-informed decision-making across its entire portfolio. This is a hybrid position based out of our Albuquerque, NM office.

The Principal Data Analyst leads the most complex and strategically significant analytical engagements, advises clients at the executive level, and sets the analytical standards and practices that define RS21's quality and differentiation in the market. Beyond delivering exceptional analytical work, this role is expected to grow the capabilities of the broader analytics team through mentorship, methodology development, and thought leadership.

The ideal candidate is a seasoned analytical practitioner who combines deep technical expertise with executive presence, intellectual curiosity, and a genuine passion for using data to solve hard problems in healthcare, government, and public-interest domains.

Key Responsibilities Advanced Analytics & Insight Delivery
  • Lead the design and execution of the most complex analytical projects, including multi-source data integration, longitudinal analysis, geospatial analysis, and statistical modeling in support of client decision-making.
  • Translate ambiguous, high-stakes business questions into rigorous analytical frameworks, ensuring methodological soundness and interpretive clarity.
  • Apply advanced statistical techniques including regression modeling, time-series analysis, clustering, hypothesis testing, and causal inference to produce defensible, high-impact findings.
  • Develop and maintain sophisticated analytical pipelines, dashboards, and reporting systems that deliver ongoing intelligence to clients and internal stakeholders.
  • Validate and quality-assure analytical outputs produced by junior and senior analysts, ensuring accuracy, reproducibility, and appropriate handling of data limitations.
  • Synthesize findings from large, complex datasets into executive-level narratives, visualizations, and recommendations that drive client action.
Technical Leadership & Standards
  • Define and champion RS21's analytical standards, including best practices for data validation, reproducible analysis, visualization design, and documentation.
  • Evaluate, recommend, and guide adoption of analytical tools, platforms, and technologies that improve team capability and delivery quality.
  • Establish code and methodology review processes that ensure consistency and excellence across the Data Analytics practice.
  • Lead the development of reusable analytical frameworks, templates, and accelerators that increase team velocity on common problem types.
  • Serve as the technical authority on analytical questions that require senior judgment, including data quality trade-offs, methodological choices, and interpretive risk.
  • Stay at the forefront of developments in data analytics, visualization, and applied statistics, bringing relevant innovations into RS21's practice.
Client & Stakeholder Engagement
  • Serve as the senior analytical relationship owner for RS21's most strategically important client accounts, building trust as a long-term advisory partner.
  • Engage directly with executive and senior client stakeholders to understand their data maturity, analytical needs, and decision-making context.
  • Lead client-facing workshops, analytical briefings, and data strategy sessions that deepen client engagement and expand the scope of analytical partnership.
  • Communicate complex analytical findings with clarity and confidence to non-technical audiences, including agency heads, program executives, and policy makers.
  • Anticipate evolving client analytical needs and proactively propose analytical approaches, capability investments, or scope expansions that deliver additional value.
  • Mentor and develop analysts at all levels within the Data Analytics practice, serving as a primary technical role model and professional development resource.
  • Lead communities of practice, peer learning sessions, and internal knowledge-sharing initiatives that elevate the team's collective analytical capability.
  • Partner with talent and HR leadership to define competency frameworks, career pathways, and hiring criteria for the Data Analytics job family.
  • Contribute to onboarding programs for new analysts, ensuring they are equipped with RS21's tools, standards, and client engagement expectations from day one.
  • Identify skill gaps across the analytics team and recommend targeted learning investments, training programs, or hiring strategies to address them.
Business Development & Organizational Strategy
  • Serve as the analytical subject matter expert on high-value and strategic proposals, shaping technical approach, staffing rationale, and differentiated win themes.
  • Contribute to capture strategy, client discovery, and competitive positioning for analytics-focused opportunities across RS21's priority markets.
  • Advise executive leadership on analytical trends, emerging client needs, and market opportunities that should inform RS21's growth strategy.
  • Represent RS21's analytical capabilities at industry conferences, client forums, and external venues through presentations, publications, or panel participation.
  • Build relationships with academic institutions, technology partners, and peer organizations that strengthen RS21's analytical ecosystem and talent pipeline.
Qualifications Required
  • Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Public Policy, or a related quantitative field. Advanced degree (Master's or PhD) strongly preferred.
  • 10+ years of progressive experience in data analysis, business intelligence, or applied analytics, including at least 3 years in a senior or lead analyst role.
  • Expert-level proficiency in SQL and at least one analytical programming language such as Python or R, including experience with libraries for data manipulation, statistical analysis, and visualization.
  • Deep experience designing and delivering complex analytical projects from problem definition through insight delivery, including work with messy, incomplete, or multi-source datasets.
  • Advanced proficiency with data visualization and business intelligence platforms such as Tableau, Power BI, Looker, or equivalent.
  • Strong grounding in applied statistics, including regression, significance testing, sampling methodology, and uncertainty quantification.
  • Proven track record of engaging and influencing executive-level stakeholders through data-driven analysis and storytelling.
  • Demonstrated experience mentoring analysts and contributing to team capability development.
Preferred
  • Advanced degree in a quantitative discipline such as Statistics, Applied Mathematics, Data Science, Public Health, or related field.
  • Experience working with federal, state, or local government clients, including familiarity with government data standards, privacy regulations (e.g., HIPAA, FERPA), and reporting requirements.
  • Background in healthcare analytics, population health, program evaluation, or social services data.
  • Experience with geospatial analysis tools such as ArcGIS, QGIS, or Python-based spatial libraries.
  • Familiarity with cloud-based data platforms such as AWS Redshift, Google BigQuery, Snowflake, or Azure Synapse.
  • Experience with longitudinal data, panel data methods, or quasi-experimental evaluation designs.
  • Published work, conference presentations, or other recognized contributions to the data analytics field.
  • Experience contributing to or leading data strategy, analytics roadmap, or data governance initiatives at an organizational level.
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