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Remote Master Data Management Jobs in Spring, TX

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Executive Assistant / Project Coordinator Land Management

The Woodlands, TX · Remote

$80K - $120K/yr

Strong data management and documentation skills. * Experience creating project schedules, timelines ... Onsite preferred in The Woodlands Remote work flexibility may be considered for candidates meeting ...

New

DIMENSIONAL ENERGY INC

Talent Community

Houston, TX · Remote

$17.25 - $23/hr

Catalysis / Material / Mechanical Engineering (Ithaca, NY / Remote) * Project Management * IT Systems and Data Management * Finance * Marketing * Business Development * HR / Administration

Datavant

Outpatient Coding Consultant - Remote

Houston, TX · Remote

$20 - $28/hr

Datavant is the data collaboration platform trusted for healthcare. Guided by our mission to make ... Communicate with co-workers, management, and hospital staff regarding clinical and reimbursement ...

GAI Consultants

Data Center Program Manager

Houston, TX · On-site +1

$112K/yr

Team Management & Mentorship * Mentor and manage multidisciplinary teams, fostering a collaborative ... Enjoy flexible work arrangements (remote/hybrid options available). * Access a comprehensive ...

Insolation Technology Ltd

Data Analyst

Houston, TX · On-site +1

$21 - $26/hr

Data Collection and Management : Gather, clean, and maintain datasets from various sources ... Flexible work schedule and remote work options Job Type: * Full time Pay: * $21.00 - $26.00 per ...

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Remote Master Data Management information

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How much do remote master data management jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for remote master data management in Spring, TX is $39.47, according to ZipRecruiter salary data. Most workers in this role earn between $27.16 and $49.18 per hour, depending on experience, location, and employer.

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

Remote Master Data Management (MDM) professionals often encounter challenges such as ensuring data consistency across multiple systems, coordinating with geographically dispersed teams, and maintaining data security. Effective communication and collaboration tools are essential for aligning with stakeholders and IT teams. Establishing clear data governance policies and regular virtual meetings can help address inconsistencies and streamline workflows. Additionally, using secure remote access solutions and adhering to best practices in data privacy ensures data integrity and compliance.

What are the key skills and qualifications needed to thrive as a remote master data management professional, and why are they important?

To thrive as a Remote Master Data Management professional, you need expertise in data governance, data quality, and master data modeling, often supported by a degree in information systems or a related field. Familiarity with MDM platforms like Informatica, SAP MDG, or Oracle, as well as knowledge of data integration tools and data security standards, is typically required. Strong analytical thinking, communication skills, and attention to detail are essential soft skills for collaborating across departments and ensuring data consistency. These competencies are crucial for maintaining accurate, reliable data assets that drive business decisions and operational efficiency.

What is a remote master data management professional?

A Remote Master Data Management (MDM) professional is responsible for overseeing and maintaining an organization's critical data assets from a remote location. They ensure the accuracy, consistency, and security of master data—such as customer, product, and supplier information—across different systems and departments. By implementing data governance policies and collaborating with various teams, they help organizations make better business decisions and comply with data regulations. Remote MDM professionals use specialized tools and processes to manage data integrity while working outside of a traditional office environment.

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

AspectRemote Master Data ManagementRemote Data Analyst
CredentialsTypically requires data management certifications, SQL, and database knowledgeRequires data analysis, Excel, SQL, and visualization skills
Work EnvironmentFocuses on data governance, quality, and integration within organizationsAnalyzes data to generate insights, reports, and support decision-making
Industry UsageCommon in IT, finance, healthcare, and large enterprisesWidely used across marketing, finance, healthcare, and consulting

Remote Master Data Management professionals focus on maintaining accurate, consistent, and reliable data across systems, while Remote Data Analysts interpret data to inform business decisions. Both roles require strong technical skills but serve different functions within organizations.

What are popular job titles related to Remote Master Data Management jobs in Spring, TX? For Remote Master Data Management jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Remote Master Data Management jobs in Spring, TX look for? The top searched job categories for Remote Master Data Management jobs in Spring, TX are:
What cities near Spring, TX are hiring for Remote Master Data Management jobs? Cities near Spring, TX with the most Remote Master Data Management job openings:
Remote Master Data Management jobs near you

Data Scientist - Remote

NAVA Software Solutions

Houston, TX • On-site, Remote

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

NAVA Software solutions is looking for a Data Scientist
Details:
Data Scientist
Location: Houston TX - Remote is ok
Duration: 12 months
Clients want a data scientist who can develop machine learning models to run forecast scenarios. Also, they want this person to be knowledgeable in AWS Cloud technology
A Data Scientist with physical pipeline experience typically specializes in analyzing and optimizing physical infrastructure pipelines, such as those used in the oil and gas industry or transportation networks. Here are some common job duties associated with this role:
  • Data collection and integration: Data scientists with physical pipeline experience gather data from various sources related to the infrastructure pipelines, such as sensors, SCADA (Supervisory Control and Data Acquisition) systems, or IoT devices. They integrate and consolidate the data for analysis and modeling.
  • Pipeline performance analysis: These professionals analyze the performance of physical pipelines by examining data related to flow rates, pressure levels, temperature, corrosion, and other relevant factors. They use statistical techniques and machine learning algorithms to identify patterns, anomalies, and potential issues that may affect pipeline operations.
  • Predictive modeling and maintenance optimization: Data scientists develop predictive models to forecast pipeline performance and detect potential failures or maintenance needs. They utilize historical data, sensor measurements, and other relevant parameters to train models that can predict future events, such as leaks, blockages, or equipment failures. By identifying critical maintenance requirements in advance, they can optimize maintenance schedules and minimize downtime.
  • Risk assessment and mitigation: Data scientists assess risks associated with physical pipelines, such as environmental hazards, security threats, or regulatory compliance. They develop risk assessment models and analyze the impact of different factors on pipeline safety and integrity. Based on these analyses, they propose mitigation strategies to minimize risks and ensure compliance with safety regulations.
  • Optimization of pipeline operations: Data scientists work on optimizing the operational efficiency of physical pipelines. They analyze data to identify areas of improvement, such as reducing energy consumption, optimizing transportation routes, or improving overall system performance. By applying data-driven approaches and algorithms, they provide recommendations to optimize pipeline operations and maximize efficiency.
  • Visualization and reporting: Data scientists with physical pipeline experience create visualizations, reports, and dashboards to communicate their findings and recommendations effectively. They present complex data in a visually understandable format, allowing stakeholders to make informed decisions regarding pipeline maintenance, operations, and risk management.
  • Collaboration with cross-functional teams: These professionals collaborate with engineers, domain experts, operations personnel, and other stakeholders involved in managing physical pipelines. They work together to understand the specific requirements, constraints, and challenges associated with the infrastructure. Effective communication and teamwork are essential to ensure alignment and successful implementation of data-driven solutions.
  • Continuous improvement and innovation: Data scientists keep up with the latest advancements in data science, machine learning, and pipeline technologies. They explore new methodologies, algorithms, and tools to enhance their skills and propose innovative solutions to address pipeline-related challenges.
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About NAVA Software Solutions

Sourced by ZipRecruiter

NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

Social media

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