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Computational Data Science Jobs in Texas (NOW HIRING)

Adidev Technologies Inc

DATA SCIENTIST

Austin, TX · On-site

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

Adidev Technologies Inc

DATA SCIENTIST

Austin, TX · Remote

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

Mindlance

Data Scientist

Houston, TX · On-site

... data science approach by developing novel and/or adapting existing computational methods • Strong skills in communicating and presenting data-derived insights to non-technical audiences ...

Mindlance

Data Scientist

Houston, TX · On-site

... data science approach by developing novel and/or adapting existing computational methods • Strong skills in communicating and presenting data-derived insights to non-technical audiences ...

Moffitt

... computational immunology, clinical trials, biomarkers, precision medicine, and next-generation ... Interdisciplinary Team Science - Work alongside leading cancer biologists, clinicians ...

New

IntelliGenesis

Senior Data Scientist

Boerne, TX · On-site

Our data-rich environment allows you to use your knowledge and experience in data science on ... Requires strong technical and computational skills - engineering, physics, mathematics, coupled ...

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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 3, 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 does a computational data scientist do?

A computational data scientist analyzes large datasets using programming languages like Python or R, develops algorithms, and applies statistical models to extract insights and solve complex problems. They often work with machine learning tools and require strong analytical skills, programming knowledge, and familiarity with data management environments.

Is computational science in demand?

Computational Data Science is in high demand across industries such as technology, finance, healthcare, and research, driven by the increasing reliance on data analysis, machine learning, and big data tools. Professionals with skills in programming, statistical analysis, and data modeling are sought after for roles involving data-driven decision making and automation.

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.

Is 40 too late for data science?

Computational Data Science is a field where individuals can enter at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning through online courses or certifications. Age is generally not a barrier if you develop the necessary technical skills and stay current with industry tools.

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, and why are they important?

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 is the highest paid job in data science?

The highest paid roles in data science are often senior positions such as Lead Data Scientist, Machine Learning Director, or Chief Data Officer, with salaries exceeding $150,000 annually. These roles typically require advanced skills in machine learning, big data tools, and leadership experience. Compensation varies by industry, location, and company size.
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 July 2026, with employment types broken down into 2% Locum Tenens, 70% Full Time, 27% Part Time, and 1% Contract. Highlights an 64% Physical, 3% Hybrid, and 33% Remote job distribution, with an average salary of $110,094 per year, or $52.9 per hour.

DATA SCIENTIST

Adidev Technologies Inc

Austin, TX • On-site

Full-time

Re-posted 13 days ago

Job description

Adidev Technologies Inc
www.adidevtechnologies.com
URGENT HIRE - HIRING PROCESS - 24-48 HOURS!
Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of candidates looking to start as soon as possible. Excellent written and oral communication are required as is the ability to work well in a team environment.
If you are looking for a new challenge and are ready to make an impact on a growing team, then this will be a perfect fit. As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients.
Adidev Technologies is a growing software consulting company that is constantly expanding. As we are working with renowned clients and ready to take on new ones, we are seeking brilliant software engineers. Not only do we offer a great team to work with, but we also offer you an opportunity to make an immediate impact and get rewarded accordingly
Job Description
  • Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation systems, environmental systems, and/or agronomic problems.
  • Strong foundation in Python programming in a cloud environment.
  • Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills
  • Expertise in data wrangling using SQL,
  • Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes
  • Fluency in querying/extracting/aggregating data via SQL scripting.
  • Extract, load and transform data (ETL) from structured and unstructured sources
  • Apply Natural Language Processing and Computer Vision to solve business use cases,
  • Strong skills in scientific data analyses, modeling, visualization and communication of results.
  • Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction
  • Ph.D., M.S. or B.S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline

Must have
  • Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
  • Regression (e.g. ? Linear/Logistic/MNL/Mixed Effects/Regularization)
  • Classification (K-means, Hierarchical, Latent Class, DBScan, SVM)
  • Dimension Reduction techniques (Principal Component analysis, Singular Value Decomposition etc.)
  • Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.)
  • Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras
  • Machine Learning algorithms? Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest
  • Distributed computing tools and cloud technology (AWS)

QUALIFICATIONS
  • Degree in Data Science, Computer Science, Engineering, Math, or Statistics preferred
  • At least 2 yrs of relevant experience in Data Science

SKILLS
  • SQL, statistical modeling, Feature engineering, Data visualization, Deploying models to production, Python programming, AWS, Domains(Healthcare/ Manufacturing/ Marketing/ Financial/ Telecommunication), powerbi/tableau, data warehouse

Benefits
  • Competitive Salary
  • Paid Relocation
  • Remote Support
  • Guaranteed Regular Salary Reviews
  • Job Type: W2 or Contract 1099 (full-time - 40 hours)

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