1

Python Data Analyst Jobs in Albuquerque, NM (NOW HIRING)

Job Overview The Strategy Analyst / Associate is a high-visibility, hands-on, and dynamic role ... other technical / data visualization skills (e.g., Python, Power BI, Tableau, SQL) * Bonus:

Prog Analyst II-Lead

Albuquerque, NM · On-site

$128K - $161K/yr

Operations Data Management (ex. Aveva PI Systems, GE Proficy Historian) * Business Intelligence and ... Python, PowerShell) * Strong understanding of SQL, and Relational Databases. * Power Utility ...

A course or 6+ months of experience in Python or comparable programming language * Proven data analysis capabilities Preferred Qualifications: * Strong problem-solving and teamwork skills

next page

Showing results 1-20

Python Data Analyst information

See Albuquerque, NM salary details

$33K

$80.1K

$131.8K

How much do python data analyst jobs pay per year?

As of Jun 25, 2026, the average yearly pay for python data analyst in Albuquerque, NM is $80,105.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,600.00 and $94,000.00 per year, depending on experience, location, and employer.

What does a Python Data Analyst do?

A Python Data Analyst leverages the Python programming language to collect, process, and analyze large sets of data. They use tools and libraries like Pandas, NumPy, and Matplotlib to clean data, perform statistical analysis, and create visualizations that help organizations make data-driven decisions. Their role often involves extracting insights from complex datasets, automating data workflows, and communicating findings to stakeholders through reports or dashboards. Python Data Analysts play a crucial part in turning raw data into actionable business intelligence.

How do Python Data Analysts typically collaborate with other departments within an organization?

Python Data Analysts often work closely with teams such as marketing, finance, and product development to provide data-driven insights that inform business decisions. They regularly participate in cross-functional meetings to understand departmental objectives, gather requirements for data analysis, and present their findings in an accessible manner. Effective communication and the ability to translate technical results into actionable recommendations are essential, as analysts often act as a bridge between technical data and non-technical stakeholders.

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

AspectPython Data AnalystData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentBusiness analytics, reporting, data cleaningAdvanced modeling, predictive analytics, research
Industry UsageFinance, marketing, healthcare, retailTech, finance, research, AI development

While both roles require Python and data analysis skills, Data Scientists typically engage in more complex modeling and machine learning, whereas Python Data Analysts focus on data cleaning, visualization, and reporting to support business decisions.

What Does a Python Data Analyst Do?

As a Python data analyst, you use the Python programming language to develop tools for data mining, analysis, and data visualization. You typically develop a script to meet the specific data needs of your client or employer. Then, you test your code and perform debugging duties before deploying it in a live environment. Some data analysts also have algorithm creation responsibilities. In this case, after creating and testing an algorithm, you use Python with your algorithm to interpret data. You also develop reports to show to your clients or employers, and you may code a web app or interface that clients can use to visualize data sets.

Are Python coders still in demand?

Python data analysts are currently in high demand due to the language's versatility in data analysis, machine learning, and automation. Skills in libraries like Pandas, NumPy, and experience with data visualization tools increase employability across various industries.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst. Many professionals successfully transition into data analysis at various ages by acquiring skills in programming languages like Python or SQL, and gaining experience with data visualization tools. Employers value skills and experience over age, and continuous learning can help you stay competitive in the field.

What are the key skills and qualifications needed to thrive as a Python Data Analyst, and why are they important?

To thrive as a Python Data Analyst, you need strong analytical skills, a solid grasp of statistics, and proficiency in Python programming, often supported by a degree in data science, mathematics, or a related field. Familiarity with data analysis libraries like pandas and NumPy, visualization tools such as Matplotlib or Seaborn, and experience with data querying languages like SQL are typically required. Attention to detail, critical thinking, and effective communication help you derive insights and present findings clearly to stakeholders. These skills and qualities are vital for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

Is Python useful for data analysts?

Python is highly useful for data analysts as it offers powerful libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization. It is widely used in the industry for automating tasks, building data pipelines, and performing statistical analysis, making it a valuable skill for the role.

Will AI replace data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, but it is unlikely to fully replace them. Data analysts are needed to interpret complex insights, make strategic decisions, and develop models that require domain expertise and critical thinking. Skills in programming, data visualization, and understanding AI tools remain valuable in this evolving field.
What are the most commonly searched types of Python Data Analyst jobs in Albuquerque, NM? The most popular types of Python Data Analyst jobs in Albuquerque, NM are:
What job categories do people searching Python Data Analyst jobs in Albuquerque, NM look for? The top searched job categories for Python Data Analyst jobs in Albuquerque, NM are:
Infographic showing various Python Data Analyst job openings in Albuquerque, NM as of June 2026, with employment types broken down into 1% Internship, 71% Full Time, 7% Part Time, 18% Contract, and 3% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $80,105 per year, or $38.5 per hour.
Sr Institutional Researcher

Sr Institutional Researcher

University of New Mexico

Albuquerque, NM • Hybrid

Other

Posted 1 hour ago


University Of New Mexico rating

8.5

Company rating: 8.5 out of 10

Based on 54 frontline employees who took The Breakroom Quiz

66th of 539 rated colleges and universities


Job description

Reporting to the Director for the Office of Institutional Analytics, with a dotted line to the Center for Teaching and Learning (CTL) Executive Director, this Institutional Researcher collects, develops, analyzes, communicates, and consults on a wide range of institutional data and other information to constituents throughout the university, to support and enhance informed decision-making, problem solving, strategic planning, policy development, and institutional self-assessment. Performs applied research and designs, executes, and evaluates wide-ranging analytical and statistical studies and/or institutional self-assessments. Operationalizes predictive and diagnostic models, design and manage data pipelines, and translate complex analyses into actionable insights that inform policy, pedagogy, and CTL programing. Designs and manages information systems and databases to support institutional research activities. Provides functional leadership, training, and guidance to other researchers, as appropriate.

This is a full-time, benefits eligible position that works onsite at the UNM Main (Albuquerque) Campus.

Note: This position is a joint appointment between the UNM Office of Institutional Analytics and the Center for Teaching and Learning (CTL). The successful candidate will need to RESIDE in Albuquerque, New Mexico before the start date. A hybrid work arrangement is possible, with at least 2 working days completed on the Albuquerque campus per week.

Interested candidates should submit a resume and cover letter for consideration. The cover letter should address your experience and career goals as a Data Analyst in the university setting. Your application will not be considered without a cover letter.

Candidates selected for an interview will be asked to prepare a presentation. Within the presentation, we would like to understand your problem-solving, technical, and communication skills. Instructions will be provided with the interview materials.

Duties and Responsibilities

1.       Acquires, manipulates, develops, and maintains longitudinal data sets, verifying accuracy and consistency over time, in the context of evolving requirements regarding reporting institutional facts.

2.       Conducts and/or consults on a wide variety of university survey research efforts; participates in and advises on survey construction, objectives and rationale, development of survey instruments, and design of survey protocol and procedures.

3.       Performs and/or advises on data reduction, statistical analysis of data, and interpretation of results; prepares or participates in the preparation and presentation of formal research reports, using R, SQL, Python, or other statistical analysis software.

4.       Prepares institutional responses to internal and/or external queries such as CTL usage metrics, student success outcomes, etc.

5.       Designs, executes, analyzes, communicates, and consults on the results of ongoing and one-time analytical studies using appropriate inferential statistics.

6.       Represents CTL and OIA in ad hoc committees, meetings, conferences, and task forces, as assigned.

7.       Provides functional direction to lower-level technicians on assigned work. May supervise student employees.

8.       Organizes and facilitates data literacy training and workshops for staff, faculty, and students.

9.       Performs miscellaneous job-related duties as assigned.

Knowledge, Skills and Abilities Required

         Knowledge of data collection for higher education settings including assessments of retention and other academic success metrics

         Proficiency with developing, designing and maintaining dynamic dashboards and visualizations, SPECIFICALLY Tableau and Power BI that communicate complex information to faculty, staff, and administrators.

         Strong interpersonal and communication skills and the ability to work effectively with a wide range of constituencies in a diverse community.

         Knowledge of higher education planning methods, processes, systems, reporting, and databases.

         Experience conducting quantitative and qualitative analyses-such as regression, hypothesis testing, and longitudinal modeling-to evaluate teaching, tutoring, and instructional interventions.

         Experience developing, testing, and refining statistical and machine learning models to identify key drivers of student learning, retention, and academic success.

         Supervising and mentoring staff and student employees involved in data collection, coding, and analysis.

         Promoting data literacy, responsible data use, and equity-focused analytics

         Ability to draw conclusions and make recommendations based on research data and findings.

         Skill in the use of personal computers and related software applications.

         Ability to communicate effectively, both orally and in writing.

         Knowledge of institutional self-assessments and student outcomes assessment principles, methods and techniques.

         Ability to provide technical leadership and direction to lower-level staff members.

         Knowledge of statistical data collection, analysis, tracking, and reporting systems, methods, and techniques.

         Proficiency working with SAS, R, Python, SQL programming and/or other software used to manipulate, summarize, and produce reports from multiple, large, complex data sets.

         Ability to analyze statistical data and generate reports, and design and administer survey instruments.

         Ability to visualize complex data analyses using data visualization software such as Tableau, PowerBI, and DataWrapper

         Ability to plan, create, program, and manage statistical computer databases across multiple hardware and operating system platforms/environments.

         Knowledge of University data systems, definitions, and procedures.

         Knowledge of statistical and analytical survey instruments, protocol, and procedures.

         Strong interpersonal and communication skills and the ability to work effectively with a wide range of constituencies in a diverse community.

Distinguishing Characteristics

Position requires: a) Performing applied research and designing, executing, and evaluating wide-ranging analytical and statistical studies; b) participating in the preparation and presentation of formal research reports; c) facilitating the development, implementation, and evaluation of integrated institutional self-assessment programs; d) facilitating the findings into institutional planning and decision-making; and e) providing functional direction to other institutional researchers and data analysts.


What University Of New Mexico employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom