2

Remote Data Science Jobs in Rockwall, TX (NOW HIRING)

Data Analyst

Dallas, TX · Remote

$23.50 - $30.50/hr

This is a remote role strictly for candidates within the United States. Position Overview: As a ... Education: * Bachelors degree in Data Science, Engineering, Statistics, Computer Science, or a ...

Peoplevisor is seeking an experienced Data Scientist who will support our product, sales ... Master's or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is ...

... data scientists, and AI engineers to translate knowledge into formal models. - Govern ontology ... The starting pay range for this remote role is $105,840.00-$147,000.00. This range reflects the ...

Showing results 21-40

Remote Data Science information

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

What are the qualifications to get a remote data science job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

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

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

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

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

Can I work remotely as a data scientist?

Yes, many data scientist roles are available as remote positions, especially in companies that prioritize flexible work arrangements. Remote data scientists typically need strong skills in programming, data analysis, and tools like Python or R, and may require familiarity with cloud platforms and collaboration tools. Availability depends on the employer's policies and the specific job requirements.

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

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

What are popular job titles related to Remote Data Science jobs in Rockwall, TX?

For Remote Data Science jobs in Rockwall, TX, the most frequently searched job titles are:

What job categories do people searching Remote Data Science jobs in Rockwall, TX look for?

The top searched job categories for Remote Data Science jobs in Rockwall, TX are:

What cities near Rockwall, TX are hiring for Remote Data Science jobs?

Cities near Rockwall, TX with the most Remote Data Science job openings:

Infographic showing various Remote Data Science job openings in Rockwall, TX as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Senior Data Engineer - Remote

Vytwo

Prosper, TX • Remote

$55 - $60/hr

Full-time

Re-posted 15 days ago


Job description

Role: Senior Data Engineer
Remote Work
*Must be a US Citizen* & have a USA Passport
Primary Responsibilities:

  • Design, develop, and maintain scalable data pipelines using Python, PySpark, and other modern programming languages to support both batch and streaming workloads.
  • Build and optimize data processing frameworks on cloud platforms such as Databricks or Snowflake, ensuring performance, reliability, and cost efficiency
  • Design and implement robust data models, including transactional (OLTP) and dimensional (OLAP) schemas, to support analytics, reporting, and application integration
  • Develop high quality SQL code including complex queries, stored procedures, and views, with a focus on performance tuning and efficient data access patterns
  • Create and manage workflow orchestration using Apache Airflow or similar tools, ensuring reliable scheduling, dependency management, and monitoring
  • Implement and enforce data governance and metadata standards through tools such as Microsoft Purview, including data lineage, classification, cataloging, and security policies
  • Build automated data quality and validation frameworks to ensure accuracy, completeness, and reliability of production datasets
  • Collaborate with cross functional teams including data architects, analysts, scientists, and business stakeholders to understand requirements and deliver scalable, well designed data solutions
  • Lead technical design sessions and code reviews, promoting engineering best practices, reusability, and maintainability
  • Support cloud infrastructure and DevOps practices, including CI/CD pipelines, version control, testing automation, and environment management
  • Monitor and troubleshoot production data pipelines, proactively addressing issues, performance bottlenecks, and system failures
  • Contribute to the evolution of the enterprise data platform, recommending tools, frameworks, and architectures to improve scalability and efficiency
You’ll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
Required Qualifications:

  • 7+ years of experience in data engineering, software engineering, or similar disciplines
  • Hands-on experience with Databricks or Snowflake
  • Experience with orchestration tools such as Apache Airflow
  • Experience working with cloud ecosystems (Azure preferred; AWS/GCP acceptable)
  • Advanced SQL skills and experience with OLTP and OLAP data modeling
  • Solid understanding of modern data warehousing, data lake, and ELT/ETL design patterns
  • Familiarity with data governance tools, especially Microsoft Purview
  • Solid programming expertise in Python, PySpark, or similar languages
  • If you are offered this position, you will be required to provide extensive personal information to obtain and maintain a suitability or determination of eligibility for a Confidential/Secret or Top Secret security clearance as a condition of your employment
  • Must be a US Citizen
Preferred Qualifications:

  • Healthcare industry experience, including claims, clinical, FHIR, HL7, or provider data
  • Experience with containerization (Docker, Kubernetes) for data workloads
  • Experience supporting machine learning workflows or analytical data science pipelines
  • Knowledge of distributed computing concepts and performance tuning

This is a remote position.