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Remote Data Management Jobs in Goodyear, AZ (NOW HIRING)

Mondo

Data Scientist

Phoenix, AZ · Remote

$65 - $75/hr

Remote (Candidate must reside in Pacific, Mountain, or Central time zone. Eastern time zone and ... Own CI/CD for ML workflows, including automated retraining, model registry management, and rollback ...

Achieve

Sr. Data Analyst

Tempe, AZ · On-site +1

Design portfolio monitoring, processes, and controls for managing credit risk and identifying root ... Hybrid and remote work opportunities * Medical, dental, and vision with HSA and FSA options Note:

Achieve

Sr. Data Analyst

Tempe, AZ · On-site +1

$115K - $145K/yr

Design portfolio monitoring, processes, and controls for managing credit risk and identifying root ... Hybrid and remote work opportunities * Medical, dental, and vision with HSA and FSA options Note:

Kemper

SVP, Chief Technology Officer (CTO)

Phoenix, AZ · On-site +1

... IL, Remote-MI, Remote-NJ, St. Louis, Missouri Details Kemper is one of the nation's leading ... Master Data Management * Enterprise data security Demonstrated expertise is required across ...

XTG

Data Engineer

Phoenix, AZ · On-site +1

$113K - $136K/yr

This opportunity is remote with the ideal candidate being located in DFW, Phoenix, Atlanta or ... Create scalable ETL/ELT processes to extract, cleanse, transform, and load data from ERP, CRM, ...

U-Haul

Contact Center Data Analyst

Phoenix, AZ · On-site +1

... remote work. As a Data Analyst, team members will be responsible for evaluating and improving U ... Collaborate with senior managers and decision makers to identify and solve a variety of problems ...

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Remote Data Management information

What are some common challenges faced in remote data management, and how can they be addressed?

One common challenge in remote data management is ensuring data security and integrity while working outside a traditional office environment. Remote team members must follow strict protocols for data access and regularly update security measures to protect sensitive information. Additionally, effective communication and collaboration with cross-functional teams can be more difficult remotely, so utilizing project management and communication tools is vital. Establishing clear workflows and regular check-ins helps maintain data consistency and team alignment.

What is remote data management?

Remote Data Management refers to the practice of organizing, storing, securing, and analyzing data from a location outside of an organization's physical premises. Professionals in this field use cloud-based tools and remote access software to manage databases, ensure data integrity, and facilitate data sharing among distributed teams. This approach enables businesses to maintain their data infrastructure efficiently while supporting remote work and global collaboration. It also involves implementing protocols to ensure data security and compliance with relevant regulations.

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

AspectRemote Data ManagementData Analyst
CredentialsTypically requires a degree in IT, Computer Science, or related fields; certifications like Microsoft Certified Data Analyst or AWS Data AnalyticsRequires a degree in Statistics, Mathematics, or related fields; certifications like Microsoft Certified Data Analyst Associate or Tableau Desktop Specialist
Work EnvironmentPrimarily remote, working with databases, data warehouses, and cloud platformsRemote or on-site, analyzing data sets, creating reports, and visualizations
Industry UsageUsed across IT, finance, healthcare, and e-commerce sectorsCommon in finance, marketing, healthcare, and consulting industries

Remote Data Management and Data Analysts share overlapping skills in data handling and analytics, but differ mainly in focus. Remote Data Management emphasizes database administration and cloud platforms, while Data Analysts focus on interpreting data and creating insights. Both roles are vital in data-driven organizations and often collaborate to optimize data use.

What are the key skills and qualifications needed to thrive in remote data management?

To thrive in Remote Data Management, you need strong analytical skills, attention to detail, and a solid understanding of database concepts, often supported by a degree in information systems or a related field. Proficiency with data management tools such as SQL, Microsoft Excel, and cloud-based platforms like AWS or Google Cloud, as well as knowledge of data privacy regulations, is typically required. Excellent communication, self-motivation, and time management are important soft skills for collaborating with distributed teams and managing tasks independently. These skills ensure accurate, secure, and efficient handling of data assets while maintaining productivity and compliance in a remote work environment.

What are remote jobs in data management?

Various types of remote data management jobs are available in healthcare and insurance, with titles like clinical data manager, analyst, and auditor. In these jobs, you manage a database and provide analysis of information related to clinical trials, medical payments, operational activities, and more. Your duties and responsibilities include generating reports, database administration, and providing support for coworkers throughout your organization, but your responsibilities can vary based on what kinds of data you store. Additionally, you work with your company’s leadership to address issues affecting the availability and use of data and proactively suggest strategies for improving efficiency and accuracy. In some roles, you also participate in project planning, resource allocation, and budgeting.

More about Remote Data Management jobs

What are the most commonly searched types of Data Management jobs in Goodyear, AZ?

The most popular types of Data Management jobs in Goodyear, AZ are:

What are popular job titles related to Remote Data Management jobs in Goodyear, AZ?

For Remote Data Management jobs in Goodyear, AZ, the most frequently searched job titles are:

What job categories do people searching Remote Data Management jobs in Goodyear, AZ look for?

The top searched job categories for Remote Data Management jobs in Goodyear, AZ are:

What cities near Goodyear, AZ are hiring for Remote Data Management jobs?

Cities near Goodyear, AZ with the most Remote Data Management job openings:

Remote Data Management jobs near you
Infographic showing various Remote Data Management job openings in Goodyear, AZ as of August 2026, with employment types broken down into 71% Full Time, and 29% Contract. Highlights an 100% Remote job distribution.

Data Scientist

Mondo

Phoenix, AZ • Remote

$65 - $75/hr

Contractor

Medical, Dental, Vision, Retirement

Posted 29 days ago

Job description

Apply now: Senior Data Scientist , Remote. Start date is ASAP for this 12 Month Contract position.

Job Title: Senior Data ScientistLocation/Type: Remote (Candidate must reside in Pacific, Mountain, or Central time zone. Eastern time zone and international candidates will not be considered.)Start Date: ASAPDuration: Contract, 6  Months (extension likely)Compensation Range: $65/hr to $75/hrBenefits: Eligible for Health, Dental, Vision, and 401KVisa Sponsorship: Not eligible for visa sponsorship

Job Description:The client is seeking a Data Scientist with deep expertise in Generative AI, agentic architectures, and MLOps to design, build, and scale end to end AI solutions while embedding Responsible AI practices across the full development lifecycle. This role requires hands on MLOps maturity, not just model building, the candidate will own how models move from experimentation into production and stay reliable once they get there.

Job Summary:

  • Design and deploy end to end RAG solutions and autonomous AI agents in cloud and enterprise environments
  • Build and scale machine learning and AI models on cloud platforms, primarily AWS or Azure
  • Develop and maintain MLOps pipelines to support model deployment, monitoring, versioning, and governance
  • Own CI/CD for ML workflows, including automated retraining, model registry management, and rollback procedures
  • Implement model monitoring for drift, performance degradation, and data quality issues in production
  • Apply statistical modeling techniques to solve complex business problems
  • Collaborate with stakeholders across the organization to translate requirements into scalable AI solutions
  • Embed Responsible AI practices across model development, deployment, and governance workflows
  • Contribute across the full development lifecycle, from experimentation through production release

Requirements:

Must Haves:

  • Location: candidate must be based in Pacific, Mountain, or Central time zone. This is a hard requirement, not a preference.
  • Minimum 4 years of experience working specifically as a Data Scientist (title and scope must match, not adjacent titles like Data Analyst or ML Engineer alone)
  • Must currently or most recently hold a Data Scientist title (Data Scientist, Senior Data Scientist, Staff Data Scientist, Principal Data Scientist, etc.). Candidates whose current or most recent role carries a different title (Data Analyst, ML Engineer, Analytics Engineer, etc.)
  • Minimum 3 years of hands on MLOps experience, specifically model deployment, monitoring, and lifecycle management in production environments (not just model development or notebooks)
  • Direct experience with at least one MLOps tooling stack such as MLflow, Kubeflow, SageMaker Pipelines, or Azure ML Pipelines
  • Master's degree in a STEM field
  • 4 years of proficiency in SQL
  • 4 years of proficiency in Python
  • Hands on experience with AWS or Azure cloud platforms
  • Proficiency with Git for version control
  • Strong communication skills with demonstrated ability to work cross functionally with stakeholders

Nice to Haves:

  • Experience with Snowflake for data warehousing and analytics
  • Hands on experience with AWS specifically, in addition to general cloud proficiency
  • Startup or fast paced environment mindset with comfort navigating ambiguity
  • Active personal use of AI tools and familiarity with the evolving AI landscape