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Data Science Entry Level Remote Jobs in Dallas, TX

Remote Hours: 10-20 hours/week Duration: 1-2 months minimum, with likely extension Start: Immediate ... Scientific Data Interpretation * Evidence-Based Reasoning * Technical Documentation Qualifications

The remote High School Science Teacher is a highly qualified, state certified educator responsible ... Student success will be measured by valid and reliable assessment data, parent and student ...

The remote Middle School Science Teacher is a highly qualified, state certified educator ... Student success will be measured by valid and reliable assessment data, parent and student ...

TEXAS The remote High School CTE Teacher in Computer Science is state certified teacher and/or ... Student success will be measured by valid and reliable assessment data, parent and student ...

Nurse Practitioner: Remote Urgent Care

Frisco, TX · Remote

$103K - $142K/yr

Belle uses cutting edge data science to identify those most in need on behalf of health plans and ... As these issues arise, a team of remote nurses coordinate care with other healthcare providers ...

Showing results 21-40

Data Science Entry Level Remote information

What is a data science entry level remote job?

Data science entry level remote jobs are positions suitable for individuals who are just starting their careers in data science and prefer or require the flexibility to work from home or any location outside the traditional office setting. These roles typically involve tasks such as data cleaning, basic statistical analysis, creating simple data visualizations, and assisting with machine learning projects under supervision. Entry level data scientists often work closely with more experienced team members and use tools like Python, R, SQL, and Excel. Remote roles require good communication skills and self-motivation, as collaboration happens online. These positions are a great way to gain practical experience and develop technical skills in the field of data science.

What skills and qualifications are needed to thrive as an entry-level remote data scientist?

To thrive as an entry-level remote Data Scientist, you need a solid background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree or certification. Familiarity with tools like Jupyter Notebook, SQL databases, and machine learning libraries such as scikit-learn or TensorFlow is commonly required. Strong problem-solving abilities, communication skills, and self-motivation are crucial soft skills for remote collaboration and project management. These competencies enable effective data-driven insights, seamless teamwork, and measurable contributions in a distributed work environment.

What challenges do entry-level data scientists face when working remotely, and how can they overcome them?

Entry-level data scientists working remotely often encounter challenges such as limited access to mentorship, difficulty in collaborating on complex projects, and adjusting to asynchronous communication. To overcome these, it's important to proactively seek guidance from senior team members through regular check-ins, participate actively in team meetings and online forums, and document your work thoroughly for transparency. Leveraging collaborative tools like shared code repositories and communication platforms can also help maintain strong connections with your team and ensure project alignment.

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

AspectData Science Entry Level RemoteData Analyst Entry Level Remote
Required CredentialsBachelor's in CS, Statistics, or related field; some knowledge of programming and machine learningBachelor's in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentRemote, collaborative teams, often with cross-functional departmentsRemote, often working independently or with business teams
Employer & Industry UsageTech companies, finance, healthcare, e-commerceBusiness, marketing, finance, healthcare

While both roles are entry-level remote positions involving data, Data Science Entry Level Remote focuses on programming, machine learning, and predictive modeling, whereas Data Analyst Entry Level Remote emphasizes data visualization, reporting, and interpreting data for business insights. Candidates should choose based on their skills and career interests.

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

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

What are popular job titles related to Data Science Entry Level Remote jobs in Dallas, TX?

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

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

The top searched job categories for Data Science Entry Level Remote jobs in Dallas, TX are:

Infographic showing various Data Science Entry Level Remote job openings in Dallas, TX as of September 2026, with employment types broken down into 55% Full Time, and 45% Part Time. Highlights an 100% Remote job distribution.

Remote Oncology Data Engineer - Precision Medicine - Dallas, Tx

Dallas, TX • On-site, Remote

The US Oncology Network
Health Care and Social Assistance • 10K+ employees

$104K - $126K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 3 days ago. Applications are no longer accepted.


US Oncology rating

7.1

Company rating: 7.1 out of 10

Based on 109 frontline employees who took The Breakroom Quiz


Job description

Overview
Texas Oncology is looking for a Remote Oncology Data Engineer to join our Precision Medicine team! This position is based out of the corporate office in Dallas, Texas. Must currently reside in Texas.
Texas Oncology is the largest community oncology provider in the country and has approximately 600+ providers in 300+ sites across Texas and southeastern Oklahoma. Our founders pioneered community-based cancer care because they believed in making the best available cancer care accessible to all communities, allowing people to fight cancer at home with the critical support of family and friends nearby. Our mission is still the same today-at Texas Oncology, we use leading-edge technology and research to deliver high-quality, high-touch, evidence-based cancer care to help our patients achieve "More breakthroughs. More victories." ® in their fight against cancer. Today, Texas Oncology treats half of all Texans diagnosed with cancer on an annual basis.
Why work for us?
Come join our team that is responsible for helping lead Texas Oncology in treating more patient diagnosed with cancer than any other provider in Texas. We offer our employees a competitive benefits package that includes Medical, Dental, Vision, Life Insurance, Short-term and Long-term disability coverage, a generous PTO program, a 401k plan that comes with a company match, a Wellness program that rewards you practicing a healthy lifestyle, and lots of other great perks such as Tuition Reimbursement, an Employee Assistance program and discounts on some of your favorite retailers.
Join a Team That Invests in Your Future
At Texas Oncology, we recognize the long-term impact of our people and are committed to rewarding performance and potential. That's why select roles may be eligible to participate in our Long-Term Incentive Plan (LTIP): an incentive program designed to attract, retain, and reward top talent.
What is the Long-Term Incentive Plan (LTIP)?
Long-Term Incentive Plan (LTIP): is an incentive program that typically vests over a three-year period and is tied to both individual performance and the operational success of Texas Oncology. Awards are discretionary and based on your position, performance, and potential for future career growth at Texas Oncology. Awards are reviewed and approved during the annual compensation review. LTIP awards are subject to your continued employment through the award payment date, and are governed by the written terms and conditions of the LTIP document.
What does the Oncology Data Engineer do?
The Oncology Data Engineer will support Precision Medicine's data delivery team, design and build robust data pipelines and implement new data architecture to support informatics decision-making. Leveraging deep understanding of ETL methodologies, and AI technologies, the Oncology Data Engineer will create scalable and efficient solutions using innovative technology, including SQL, OpenAI tools and large language models (LLMs). Supports and adheres to US Oncology Compliance Program, to include the Code of Ethics Business Standards.
Responsibilities
The essential duties and responsibilities (included but not limited to):
Data Delivery Support
  • Design, develop, and maintain robust ETL pipelines for large-scale data ingestion and transformation from various sources such as Electronic Medical Records (EMRs), lab interfaces, and data warehouses.
  • Support data science initiatives with SQL coding from various data warehouses.
  • Implement new data architecture, drawing inspiration from existing pipelines.
  • Optimize ETL workflows for performance and accuracy, ensuring seamless data integration.

AI and LLM Integration
  • Integrate AI functionalities into data platforms using OpenAI tools and LLMs.
  • Collaborate with AI teams to implement AI-driven solutions within the data pipeline.
  • Stay updated on the latest advancements in AI and LLM technologies to enhance platform capabilities.

Collaboration and Support
  • Collaborate with cross-functional teams to understand requirements and translate them into technical solutions.

Monitoring and Maintenance
  • Implement monitoring and alerting systems to proactively identify and resolve platform issues.
  • Perform regular maintenance, updates, and upgrades to cloud infrastructure and associated services.

Documentation and Best Practices
  • Maintain comprehensive documentation of system architectures, processes, and procedures.
  • Advocate for and implement best practices in cloud engineering, SQL coding, ETL processes, and AI integration.

Qualifications
The ideal candidate will have the following background and experience:
Education
  • Bachelor's or master's degree in computer science, engineering, or a related field.

Healthcare & Oncology Domain Knowledge
  • Understanding of oncology workflows and clinical data types
  • Familiarity with molecular/genomic data (e.g., NGS, variants, biomarkers)
  • Experience integrating laboratory, pathology, and molecular testing data
  • Knowledge of healthcare data standards (HL7, FHIR, ICD-10, LOINC, SNOMED)
  • Experience working with EHR data (e.g., IKMg1/IKMg2, Epic, Copia)

Experience
  • 7-10 years of professional experience in data engineering with a focus on ETL processes
  • Minimum 3+ years of professional experience in data engineering in Healthcare.
  • Strong background in cloud platforms (e.g., AWS, Azure, GCP).
  • Experience with OpenAI tools and integrating AI functionalities, including LLMs, into data platforms.

Technical Skills
  • Strong scripting and automation skills (e.g., Python).
  • Strong experience with SQL required.
  • Experience with GitHub, Confluence, Jira preferred

Soft Skills
  • Excellent problem-solving abilities and attention to detail.
  • Effective communication and teamwork skills.
  • Ability to manage multiple priorities in a challenging environment.

Physical Demands:
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations will be offered to enable individuals with disabilities to perform the essential functions. Requires sitting for long periods of time. Some bending and stretching are required. Adequate finger dexterity and feeling to perform keyboarding and substantial repetitive motions involving the wrists, hands and/or fingers. Requires vision and hearing corrected to normal range. Must be able to view computer screens and printed material accurately. Occasionally lifts and carries items weighing up to 40 lbs.
Work Environment:
The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations will be offered to enable individuals with disabilities to perform essential functions. The work environment is typical of an office setting.

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