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Independent Contractor Data Science Jobs in Houston, TX

The ideal candidate combines strong fundamentals in applied mathematics and data science with the ... Self-starter, Curious, ability to research independently and integrate knowledge from various ...

You will partner closely with business and technical stakeholders to translate data science into ... Ability to drive projects independently from ideation to deployment. * Strong business acumen with ...

... science, process) to transform structured and unstructured data into meaningful and actionable ... Exercises independent judgment within defined parameters. Responsibilities: * Participates in the ...

Bachelor's Degree in science, engineering, computer science, mathematics, statistics, or related ... Exhibits strong project management skills, with an ability to work independently on multiple ...

... data science tools and vendors. • Ensure compliance with organizational standards and policies ... independently and meet deadlines. • Strong project management and client-handling skills. • ...

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field (PhD ... Ability to work independently and collaboratively in fast-paced environments * Proven ability to ...

Data Science & Analysis Travel Required: Up to 10% Clearance Required: Ability to Obtain Public ... Ability to work in a fast-paced environment independently to produce high-quality deliverables on ...

Showing results 21-40

Independent Contractor Data Science information

What is the difference between Independent Contractor Data Science vs Data Scientist?

AspectIndependent Contractor Data ScienceData Scientist
CredentialsTypically requires a degree in data science, statistics, or related field; certifications like CAP, Microsoft Certified Data Scientist are commonUsually holds a degree in data science, statistics, or computer science; advanced certifications are a plus
Work EnvironmentFreelance, project-based, often remoteFull-time employment, office or remote
Employer & Industry UsageHired by multiple clients or companies on a contract basis; common in consulting and freelance platformsEmployed by a single organization; used across industries like tech, finance, healthcare

Independent Contractor Data Science professionals typically work on a project basis, often remotely, and serve multiple clients. Data Scientists are usually employed full-time by organizations, with a focus on ongoing data analysis and model development. Both roles require similar credentials but differ mainly in employment structure and work environment.

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

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

Infographic showing various Independent Contractor Data Science job openings in Houston, TX as of June 2026, with employment types broken down into 50% Part Time, and 50% Contract. Highlights an 100% In-person job distribution.

Lead Data Scientist - Healthcare Analytics & Machine Learning

MaxIT Consulting - Max Corporate Group

Houston, TX • Remote

Full-time

Posted 2 days ago

New


Job description

Lead Data Scientist – Healthcare Analytics & Machine Learning

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.