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Computational Data Science information

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How much do computational data science jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for computational data science in Texas is $52.93, according to ZipRecruiter salary data. Most workers in this role earn between $43.46 and $62.69 per hour, depending on experience, location, and employer.

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

AspectComputational Data ScienceData Analyst
Required CredentialsTypically requires a degree in Computer Science, Data Science, or related fields; often includes programming certificationsUsually requires a degree in Statistics, Business, or related fields; may include basic data analysis certifications
Work EnvironmentInvolves programming, modeling, and developing algorithms; often in tech or research settingsFocuses on interpreting data, creating reports, and supporting decision-making; in business or corporate environments
Employer & Industry UsageUsed in tech companies, research institutions, and industries requiring advanced modelingCommon in finance, marketing, healthcare, and business sectors

Computational Data Science involves advanced programming, algorithm development, and modeling, often in technical environments. Data Analysts focus on interpreting data, generating reports, and supporting business decisions. While both roles work with data, Computational Data Scientists typically require stronger programming skills and work on building models, whereas Data Analysts focus on data interpretation and visualization.

What is computational data science?

Computational Data Science is an interdisciplinary field that combines computer science, statistics, and domain knowledge to extract insights and knowledge from complex data sets using computational techniques. Professionals in this field use algorithms, machine learning, and advanced analytics to solve real-world problems by processing and interpreting large volumes of data. The work often involves programming, data modeling, and visualization, making it crucial in industries such as healthcare, finance, and technology. Computational Data Scientists help organizations make data-driven decisions and innovate through predictive modeling and data analysis.

What are some common challenges faced by computational data scientists when working on cross-functional teams?

Computational data scientists often collaborate closely with professionals from diverse backgrounds, such as software engineers, domain experts, and business stakeholders. One common challenge is translating complex technical findings into actionable insights for non-technical team members. Additionally, aligning project goals and expectations across disciplines can require extra communication and flexibility. Overcoming these challenges often involves developing strong interpersonal skills, proactively clarifying requirements, and fostering a collaborative team culture.

What are the key skills and qualifications needed to thrive as a computational data scientist?

To thrive as a Computational Data Scientist, you need a strong background in mathematics, statistics, programming (especially Python or R), and data analysis, often supported by a relevant degree in computer science, statistics, or a related field. Proficiency with data manipulation tools (like Pandas, NumPy), machine learning frameworks (such as TensorFlow or Scikit-learn), and cloud computing platforms is highly valued, along with experience using data visualization tools. Critical thinking, problem-solving, communication, and collaboration skills make someone stand out in this role. These abilities are crucial for extracting actionable insights from complex data, building effective models, and communicating findings to drive informed business decisions.
What are popular job titles related to Computational Data Science jobs in Texas? For Computational Data Science jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Computational Data Science jobs in Texas look for? The top searched job categories for Computational Data Science jobs in Texas are:
Computational Data Science jobs near you
Infographic showing various Computational Data Science job openings in Texas as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $110,094 per year, or $52.9 per hour.

Computational Biologist - AI Reviewer

micro1 AI

Lewisville, TX • On-site, Remote

$90 - $120/hr

Part-time

Posted 11 days ago

Job description

Role Title: Computational Biology Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology Experts to contribute their advanced scientific knowledge to a dynamic customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry.
  2. Provide feedback and domain-specific insights to improve AI models in computational biology contexts.
  3. Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with industry standards.
  4. Develop and review problem sets, case studies, or scenarios based on real-world medicinal chemistry challenges.
  5. Collaborate asynchronously with other experts to validate findings and share perspectives on project deliverables.
  6. Contribute to the refinement of data curation methodologies and best practices in computational biology.


Preferred Qualifications

  1. Advanced degree (PhD, PharmD, or MSc) in computational biology, medicinal chemistry, bioinformatics, or a closely related field.
  2. Demonstrated expertise in medicinal chemistry, including experience with drug discovery or design.
  3. Strong analytical skills with a deep understanding of biological datasets and scientific literature.
  4. Experience applying computational methods to solve problems in chemistry or biology.
  5. Proficiency with relevant bioinformatics tools, cheminformatics platforms, or data analysis software.
  6. Excellent written communication skills to clearly explain complex scientific concepts to diverse audiences.
  7. Previous participation in cross-disciplinary or AI-driven scientific projects is a plus.

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