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Remote Data Science R Jobs in Texas (NOW HIRING)

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 ...

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... Proficiency in statistical programming languages such as R, Python, SAS, or similar, alongside ...

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... Proficiency in statistical programming languages such as R, Python, SAS, or similar, alongside ...

Data Science is a driver of significant competitive advantage for Kemper and is critical to the ... Remote options are available for non-local candidate. * The range for this position is $93,300 to ...

Data Analyst

Houston, TX · On-site +1

$21 - $26/hr

Bachelors degree in Data Science, Statistics, Mathematics, Engineering, or a related field ... Proficiency in data analysis tools such as SQL, Python, R, or similar programming languages.

... and remote work on Fridays Who we're looking for: Toyota Financial Services is seeking highly ... This role is ideal for someone who will thrive working at the intersection of computational science ...

Showing results 41-60

Remote Data Science R information

What is the difference between Remote Data Science R vs Remote Data Analyst?

AspectRemote Data Science RRemote Data Analyst
Required SkillsStatistical analysis, R programming, data modeling, machine learningData visualization, basic statistical analysis, Excel, SQL
CertificationsR certifications, data science certificates, possibly advanced degreesData analysis certifications, Excel, SQL courses
Work EnvironmentCollaborative teams, research projects, data science platformsReporting, dashboards, business insights
Industry UsageTech, finance, healthcare, research institutionsMarketing, retail, finance, operations

Remote Data Science R roles focus on advanced statistical modeling and machine learning using R, often requiring specialized certifications and working on complex data projects. Remote Data Analysts typically handle data reporting, visualization, and basic analysis to support business decisions. While both roles involve data handling, Data Science R positions demand deeper technical expertise and programming skills.

What is a remote data science R?

Remote Data Science R jobs are positions that involve using the R programming language to analyze and interpret data, build statistical models, and generate insights, all while working from a remote location. These roles typically require strong skills in data manipulation, visualization, and statistical analysis using R. Professionals in these positions may work for companies in various industries, collaborating with teams online and leveraging cloud-based tools. Remote Data Science R jobs offer flexibility, allowing individuals to work from home or anywhere with a reliable internet connection.

What are the key skills and qualifications needed to thrive as a remote data science R, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, expertise in statistics, programming (Python or R), and typically a degree in data science, computer science, or a related field. Familiarity with data analysis tools, machine learning frameworks (like TensorFlow or scikit-learn), and cloud platforms (such as AWS or Google Cloud) is commonly required. Outstanding problem-solving, self-motivation, and effective virtual communication skills help you excel in remote environments. These abilities are essential for deriving actionable insights from data and collaborating efficiently across distributed teams.

How do remote data science R professionals typically collaborate with cross-functional teams while working from different locations?

Remote Data Science R professionals often use a combination of communication platforms (like Slack, Microsoft Teams, or Zoom) and project management tools (such as Jira or Trello) to stay connected with colleagues in engineering, product management, and business analysis. Sharing code and models through version control systems (like Git) and documenting workflows in shared repositories helps maintain transparency and collaboration. Regular virtual meetings and presentations are crucial for aligning goals, discussing progress, and receiving feedback. This collaborative approach ensures that data-driven insights effectively support organizational objectives, even in a distributed work environment.

What are the most commonly searched types of Data Science R jobs in Texas?

The most popular types of Data Science R jobs in Texas are:

What cities in Texas are hiring for Remote Data Science R jobs?

Cities in Texas with the most Remote Data Science R job openings:

Full-time

Re-posted 26 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)

Employment Type: FULL_TIME