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Remote Data Mining Jobs in Houston, TX (NOW HIRING)

Data Analyst

Houston, TX · On-site +1

$21 - $26/hr

Knowledge of machine learning algorithms and data mining techniques. * Familiarity with project ... Flexible work schedule and remote work options Job Type: * Full time Pay: * $21.00 - $26.00 per ...

... mining techniques, etc. * Experience with most or all of the following basic data science tools ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

Data Privacy Analyst Job Type: Contractor Location: Remote Job Overview We are seeking experienced Data Privacy Analysts to support a data privacy and AI training project focused on protecting ...

AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative ...

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Remote Data Mining information

See Houston, TX salary details

$43.9K

$157.6K

$232.5K

How much do remote data mining jobs pay per year?

As of Sep 8, 2026, the average yearly pay for remote data mining in Houston, TX is $157,588.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,500.00 and $162,300.00 per year, depending on experience, location, and employer.

What is remote data mining?

A Remote Data Mining job involves extracting, processing, and analyzing large datasets to uncover patterns, trends, and insights—all while working from a remote location. Professionals in this field use statistical methods, machine learning techniques, and specialized software to transform raw data into actionable insights. These roles are common in industries like finance, marketing, healthcare, and e-commerce, where data-driven decision-making is essential. Remote data miners typically collaborate with teams via digital communication tools and may need proficiency in programming languages like Python or R.

What skills and qualifications are needed for remote data mining?

To thrive as a Remote Data Mining professional, you need strong analytical abilities, statistical knowledge, proficiency in programming languages such as Python or R, and a background in computer science, data science, or a related field. Expertise in data mining tools like SQL, RapidMiner, or Weka and familiarity with data visualization platforms are highly valued, and certifications in data analytics can be advantageous. Attention to detail, problem-solving skills, and effective communication are important soft skills for collaborating remotely and presenting insights to stakeholders. These skills enable you to extract valuable patterns and insights from large datasets while working independently and aligning with organizational goals.

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

Remote data mining professionals often encounter challenges such as managing large and complex datasets, ensuring data privacy, and maintaining effective communication with distributed teams. Addressing these challenges typically involves leveraging secure cloud storage solutions, utilizing robust data analysis tools, and adopting clear documentation and regular virtual meetings to stay aligned on project goals. Additionally, building strong time management habits and being proactive in seeking feedback from team members can help remote data miners stay productive and engaged. Most organizations provide access to collaboration platforms and training to help overcome these obstacles, ensuring a supportive and efficient remote work environment.

How do you become a remote data mining?

To become a remote data miner, you typically need a strong foundation in data analysis, statistics, and programming languages such as Python or R. Gaining experience with data mining tools, databases, and machine learning techniques, along with relevant certifications or degrees, can improve your chances of securing a remote position in this field.

What are the most commonly searched types of Data Mining jobs in Houston, TX?

The most popular types of Data Mining jobs in Houston, TX are:

What job categories do people searching Remote Data Mining jobs in Houston, TX look for?

The top searched job categories for Remote Data Mining jobs in Houston, TX are:

What cities near Houston, TX are hiring for Remote Data Mining jobs?

Cities near Houston, TX with the most Remote Data Mining job openings:

Infographic showing various Remote Data Mining job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $157,588 per year, or $75.8 per hour.

Lead Data Scientist

MaxIT Consulting - Max Corporate Group

Houston, TX • Remote

Full-time

Posted 6 days ago


Key responsibilities

  • Lead high-priority data science and advanced analytics initiatives with organization-wide impact.

  • Analyze complex, large-scale structured and unstructured data sets using advanced statistical and analytical techniques.

  • Partner with cross-functional teams and internal stakeholders to identify business requirements and analytical opportunities.


Job description

Lead Data Scientist

United States | Remote within GA, LA, OK, TN or TX | Direct Hire

The Opportunity

A large healthcare organization is seeking an experienced Lead Data Scientist to lead advanced analytics initiatives involving complex structured and unstructured data.

This role combines hands-on data science, statistical modeling, machine learning, stakeholder engagement, and technical leadership. The successful candidate will partner with cross-functional teams to translate complex business challenges into analytical solutions and deliver actionable insights that support data-driven decision-making.

The position reports to the Manager of Data Science and includes responsibility for leading high-priority projects, mentoring other data scientists, and presenting analytical findings to senior leadership.

Key Responsibilities
  • Lead high-priority data science and advanced analytics initiatives with organization-wide impact.
  • Analyze complex, large-scale structured and unstructured data sets using advanced statistical and analytical techniques.
  • Develop custom data models and algorithms to address business questions and improve operational performance.
  • Build and apply predictive models and analytical approaches to key business metrics.
  • Conduct research, statistical analysis, modeling, data mining, visualization, and pattern analysis.
  • Develop and test hypotheses and translate findings into clear, actionable recommendations.
  • Maintain existing analytical models and evaluate model performance and goodness of fit.
  • Partner with cross-functional teams and internal stakeholders to identify business requirements and analytical opportunities.
  • Identify, investigate, and resolve complex data quality and data availability issues.
  • Improve the efficiency, scalability, and reliability of data processes.
  • Manage multiple small and medium-sized analytical engagements and competing priorities.
  • Provide technical guidance, coaching, and mentoring to other data scientists.
  • Help educate broader audiences on data science capabilities, techniques, and developments.
  • Communicate complex analytical concepts to both technical and non-technical stakeholders.
  • Present analytical findings and recommendations to senior leadership.
  • Assist in evaluating data science tools, platforms, and vendors.
Required Qualifications
  • Bachelor's Degree in Science, Engineering, Computer Science, Mathematics, Statistics, or another related STEM discipline.
  • Minimum of 7 years of professional Data Science experience.
  • Strong business analytical capabilities, including process analysis, modeling, spreadsheets, procedures, and analytical problem-solving.
  • Strong understanding of data architecture and design principles.
  • Advanced analytical reasoning, problem-solving, and decision-making skills.
  • Demonstrated ability to independently investigate complex problems and identify the information necessary to reach sound conclusions.
  • Ability to manage multiple initiatives with competing priorities while meeting project goals and deadlines.
  • Excellent written and verbal communication skills.
  • Ability to explain complex technical and analytical information to both technical and business audiences.
  • Strong stakeholder management and client-facing capabilities.
  • Ability to work independently with minimal supervision in a fast-paced, multidisciplinary environment.
  • Strong ability to troubleshoot issues, recommend solutions, and manage challenging stakeholder situations.
Required Technical & Analytical Experience

Candidates should demonstrate strong practical knowledge of:

  • Machine learning techniques, including:
    • Clustering
    • Decision tree learning
    • Artificial neural networks
    • Understanding of the practical advantages and limitations of different modeling approaches
  • Advanced statistical techniques and concepts, including:
    • Regression
    • Statistical distributions
    • Statistical testing
    • Time series forecasting
    • A/B testing
    • Clustering
  • Predictive modeling and advanced analytics.
  • Data mining, visualization, and pattern analysis.
  • Advanced SQL and database management tools.
  • Programming for analytical and data science applications.
  • Statistical analysis tools.
  • The full data science project lifecycle.
  • Analysis of large, complex, and incomplete data sources.
  • Model evaluation and interpretation of analytical results.
Leadership & Stakeholder Management

The ideal candidate will be able to combine technical depth with strong business communication.

The role requires the ability to:

  • Translate complex data into meaningful business insights.
  • Gather requirements directly from stakeholders.
  • Build compelling, evidence-based data stories.
  • Present findings confidently to senior and executive leadership.
  • Lead cross-functional analytical initiatives.
  • Mentor and provide technical guidance to less experienced data science professionals.
  • Translate complex findings into clear recommendations for a broad range of stakeholders.
Preferred Experience

The following experience is preferred but not required:

  • Master's Degree in Data Science.
  • Professional experience within a hospital or healthcare environment.
  • Medical informatics.
  • Healthcare information technology.
  • Healthcare finance or revenue cycle data management.
  • Electronic Health Record (EHR) data management.
Candidate Profile

The strongest candidate will combine advanced quantitative expertise with strong business judgment and communication skills.

They should be comfortable moving from raw and incomplete data through statistical analysis and modeling, identifying meaningful insights, and ultimately presenting those findings in a concise and actionable manner to senior stakeholders.

A strong analytical mindset, executive-level communication capability, project ownership, and the ability to mentor others are important for success in this position.

Work Arrangement

This opportunity is remote, but candidates must be able to work from one of the following states:

  • Georgia
  • Louisiana
  • Oklahoma
  • Tennessee
  • Texas

Travel of up to 20% may be required.

Work Authorization

Some visa sponsorship arrangements may be supported for this opportunity. Eligibility should be evaluated based on the individual candidate's circumstances.