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Data Science Associate Jobs in Albuquerque, NM (NOW HIRING)

MELE Associates

Engineer Scientist 3

Albuquerque, NM

MELE Associates, Inc. is seeking to add an experienced Engineer/Scientist to support the National ... Processes associated with data collection, analysis, and dissemination of information gathered by ...

MELE Associates

Engineer Scientist 5

Albuquerque, NM

MELE Associates, Inc. is seeking to add an experienced Engineer/Scientist to support the National ... Salaries are determined based on several factors including external market data, internal equity ...

MELE Associates

Engineer Scientist 2

Albuquerque, NM · On-site

MELE Associates, Inc. is seeking to add an experienced Engineer/Scientist to support the National ... Salaries are determined based on several factors including external market data, internal equity ...

MELE Associates

Engineer Scientist 6

Albuquerque, NM · On-site

MELE Associates, Inc. is seeking to add an experienced Engineer/Scientist to support the National ... Salaries are determined based on several factors including external market data, internal equity ...

Mele Accociates

Engineer Scientist 3

Albuquerque, NM · On-site

MELE Associates, Inc. is seeking to add an experienced Engineer/Scientist to support the National ... Processes associated with data collection, analysis, and dissemination of information gathered by ...

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All JobsData Science Associate JobsData Science Associate Jobs in Albuquerque, NM

Data Science Associate information

See Albuquerque, NM salary details

$55.7K

$65.9K

$125K

How much do data science associate jobs pay per year?

As of Jul 29, 2026, the average yearly pay for data science associate in Albuquerque, NM is $65,943.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,200.00 and $57,700.00 per year, depending on experience, location, and employer.

How does a Data Science Associate typically collaborate with other departments or teams within an organization?

Data Science Associates frequently work cross-functionally, partnering with teams such as engineering, product management, and business analytics to understand project requirements, share findings, and implement data-driven solutions. Collaboration often involves translating complex data results into actionable insights for non-technical stakeholders, ensuring alignment on project goals and deliverables. This role requires strong communication skills, as associates routinely participate in meetings, present analyses, and gather feedback to refine their models or analyses. Effective teamwork helps ensure that data science initiatives support broader business objectives.

Is 40 too late for data science?

Age is not a barrier to becoming a data science associate; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Is an Associates in data science worth it?

An associate's degree in data science can provide foundational skills in data analysis, programming, and statistics, which may help entry-level candidates qualify for junior data science roles. However, many employers prefer candidates with a bachelor's degree or higher, and practical experience or certifications in tools like Python, R, or SQL can enhance job prospects. The value depends on career goals and the specific requirements of potential employers.

What can I do with an associate's degree in data science?

A Data Science Associate with an associate's degree can work as a data analyst, supporting data collection, cleaning, and basic analysis using tools like Excel, SQL, and Python. They often assist in generating reports, visualizations, and insights under supervision, and may pursue certifications to enhance their skills for more advanced roles.

What are Data Science Associates?

Data Science Associates are early-career professionals who support data-driven projects by collecting, cleaning, analyzing, and interpreting large datasets. They typically work under the guidance of more experienced data scientists and help build predictive models, generate reports, and provide insights to inform business decisions. This role often requires proficiency in programming languages like Python or R, familiarity with statistical methods, and strong problem-solving skills. Data Science Associates play a crucial part in transforming raw data into actionable information for organizations.

What is the role of an associate data scientist?

An associate data scientist supports data analysis and modeling tasks by cleaning and processing data, developing algorithms, and creating visualizations. They often work under supervision to assist in building predictive models and may use tools like Python, R, or SQL to analyze data and generate insights.

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

To thrive as a Data Science Associate, you need strong analytical skills, a solid foundation in statistics and mathematics, and proficiency in programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with machine learning frameworks, data visualization tools, and database systems such as SQL is typically required. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate complex data insights into actionable business strategies. These skills are vital for extracting meaningful value from data and supporting data-driven decision-making within organizations.

What is the difference between Data Science Associate vs Data Analyst?

AspectData Science AssociateData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; often no advanced certifications required
Work EnvironmentCollaborates with data scientists and engineers; involved in building models and algorithmsFocuses on data collection, cleaning, and reporting; supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for data-driven projectsCommon across various industries for business insights and reporting

The Data Science Associate role typically involves more technical work like building models and applying machine learning, whereas Data Analysts focus on interpreting data and creating reports. Both roles require strong analytical skills, but Data Science Associates often have a deeper understanding of programming and statistical modeling.

What are the most commonly searched types of Data Science jobs in Albuquerque, NM? The most popular types of Data Science jobs in Albuquerque, NM are:
What are popular job titles related to Data Science Associate jobs in Albuquerque, NM? For Data Science Associate jobs in Albuquerque, NM, the most frequently searched job titles are:
What job categories do people searching Data Science Associate jobs in Albuquerque, NM look for? The top searched job categories for Data Science Associate jobs in Albuquerque, NM are:
What cities near Albuquerque, NM are hiring for Data Science Associate jobs? Cities near Albuquerque, NM with the most Data Science Associate job openings:
Data Science Associate jobs near you
Infographic showing various Data Science Associate job openings in Albuquerque, NM as of July 2026, with employment types broken down into 1% As Needed, 64% Full Time, 31% Part Time, 2% Temporary, and 2% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $65,943 per year, or $31.7 per hour.

IT Data Platform Data Engineer (2 Openings)

PNM Resources

Albuquerque, NM • On-site

$128K - $161K/yr

Full-time

Re-posted just now

Job description

POSTING DEADLINE
This position is posted until filled.
JOB DESCRIPTION
IT Data Platform Data Engineer
Salary Grade: G05
Minimum Midpoint Maximum
$94,831 - $128,022 - $161,213
The following statements are intended to describe the general nature and level of work being performed. They are not intended to be construed as an exhaustive list of all responsibilities, duties, and skills.
SUMMARY
Under limited direction, leads the design, build, and maintenance of enterprise-scale data pipelines and data platforms that enable advanced analytics, reporting, and AI initiatives. Partners with business and IT leadership to shape strategic data requirements, ensure robust data integration, and deliver timely access to high-quality data across the organization. Champions data engineering best practices, drives governance and security compliance, and leads continuous improvement of enterprise data infrastructure.
ESSENTIAL DUTIES AND RESPONSIBILITIES.
Leads the design, development, and maintenance of automated data pipelines for ingesting, transforming, and storing complex structured and unstructured data from multiple evolving sources
Drives collaboration with BTS and business leadership to architect reliable, scalable enterprise data solutions supporting analytics, reporting, and AI use cases
Architects, builds, and oversees data integration processes, ETL/ELT workflows, and orchestration frameworks to ensure availability, performance, and resilience
Establishes and enforces data quality, completeness, accuracy, and timeliness through advanced validation, proactive monitoring, and remediation processes
Defines and implements sophisticated data models and structures optimized for enterprise analytics and advanced analysis
Guides strategy for cloud and on-premises data platforms, including data lakes, data warehouses, and next-generation analytics environments
Leads and mentors data analysts, data scientists, and junior engineers in feature engineering and model readiness
Develops and governs metadata management, lineage, and documentation standards while driving adoption across the enterprise
Owns compliance with data security, privacy, and regulatory requirements in alignment with enterprise policies
Leads performance tuning, capacity planning, and optimization efforts for data pipelines and data storage
Oversees platform health and proactively resolves complex, systemic data pipeline issues
Authors and maintains advanced data engineering designs, standards, and operational procedures
Exercises expert judgment in evaluating technical options, balancing cost, performance, scalability, security, and maintainability
Identifies and drives innovation opportunities to modernize and expand enterprise data platforms
COMPETENCIES
Expert understanding of enterprise data architecture, integration patterns, and large scale data platforms
Demonstrates mastery of SQL and expert proficiency in Python, data modeling, and data integration tools
Diagnoses and resolves complex data flows, system dependencies, and platform level issues
Evaluates technical solutions strategically, considering long term scalability, cost, performance, and risk
Champions innovation, challenges assumptions, and leads adoption of emerging technologies
Leads and influences across matrixed organizations, driving consensus and alignment
Facilitates enterprise coordination across data, analytics, engineering, and IT functions
Defines, institutionalizes, and enforces engineering standards, best practices, and architectural guidelines
Communicates persuasively with technical teams and executive audiences
Interprets complex technical and business documentation and converts it into actionable engineering plans
Rapidly acquires, unlearns, and instills advanced tools, frameworks, and engineering methodologies
Builds trust with internal partners and cross functional teams through credibility and technical authority
QUALIFICATIONS
Bachelors degree in Computer Science, Information Systems, Engineering, or related field, with seven to nine years of progressively responsible experience in data engineering, data integration, or analytics platforms, or an equivalent combination of advanced education and experience.
A masters degree or specialized certifications preferred
CERTIFICATES, LICENSES AND REGISTRATIONS (Preferred)
Microsoft Certified: Power BI Data Analyst Associate
Tableau Desktop Certified Associate
IBM Data Analyst Professional Certificate
SAS Certified Advanced Analytics Professional (Using SAS 9)
Data Science Council of America (DASCA)
Databricks Certified Data Analyst Associate
Google, AWS, Microsoft Azure Data Analytics certifications
WORK ENVIRONMENT AND PHYSICAL REQUIREMENTS
Office environment.
Travel approximately 10% of the time.
Ability to sit, stand, walk, and stoop as required.
Manual dexterity and good vision required.
Must occasionally lift and/or move up to 10 pounds.
SAFETY AND ADA STATEMENT
Safety Statement:
Safety is a core value at (TXNM Energy/PNM/TNMP) and our vision, "everyone goes home safe", reflects our commitment to promoting an environment conducive to learning, improving and building safety practices. Our safety value is built upon the belief that every employee deserves to work in an environment free from harm.
Americans with Disabilities Act (ADA) Statement:
If you require assistance with the job application process due to a disability, please contact HR ADA Analyst, at 505-241-4627.
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