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Data Science Entry Level Remote Jobs in Texas (NOW HIRING)

Sr/Staff Data Scientist (Remote - US)

TX · On-site +1

$165K - $300K/yr

Remote US Anticipated Start Date: 06/01/2026 The US base salary range for this full-time position ... Apply data science skills to analyze large, complex datasets and identify meaningful patterns that ...

Decision Scientist

El Paso, TX · On-site +1

$40/hr

... remote work and setting your own schedule. We are looking for experienced quantitative ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

The Data Analyst will be primarily responsible for Data Analysis, Remote statistical analysis ... Bachelor's degree in Mathematics, Statistics, Computer Science, or related field. * 2-3 years of ...

The Data Analyst will be primarily responsible for Data Analysis, Remote statistical analysis ... Bachelor's degree in Mathematics, Statistics, Computer Science, or related field. * 2-3 years of ...

We are looking for a Data Scientist to join our team to train AI models. You will measure the ... Computer Science. Benefits This is a full-time or part-time REMOTE position You'll be able to ...

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Data Science Entry Level Remote information

What are the key skills and qualifications needed to thrive as an entry-level remote Data Scientist, and why are they important?

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 are some typical challenges 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 are data science entry level remote jobs?

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 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 Texas? The most popular types of Data Science Remote jobs in Texas are:
What are popular job titles related to Data Science Entry Level Remote jobs in Texas? For Data Science Entry Level Remote jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Science Entry Level Remote jobs in Texas look for? The top searched job categories for Data Science Entry Level Remote jobs in Texas are:
What cities in Texas are hiring for Data Science Entry Level Remote jobs? Cities in Texas with the most Data Science Entry Level Remote job openings:

R&D Data Scientist: Mathematical Modeling and Optimization

Liftlab Analytics, Inc.

Austin, TX • On-site, Remote

Full-time

Posted 8 days ago


Job description

(Fully-remote US position)
About LiftLab

Liftlab is the leading provider of science-driven software to optimize marketing spend and predict revenue for optimal spend levels. We call this the Science of Marketing Effectiveness. Our platform combines economic modeling with specialized media experimentation so brands and agencies can clearly see the tradeoffs of growth and profitability. With decades of experience in marketing analytics and data science, our team of industry experts and thought leaders is proud to enable leading and emerging brands such as Cinemark, Express, Hanna Anderson, Lulu & Georgia, Pandora, Sephora, Skims, Tory Burch, Thrive, and Vionic, with our cutting-edge solutions and strategic guidance.
Job responsibilities
  • Develop new algorithm-based features of LiftLab's marketing measurement and optimization platform
  • Performs diagnostics and root-cause analysis and provide fixes
  • Works with Data Science and Engineering to implement these features into LiftLabs product and workflow
Course work/experience:
  • Data manipulation
    • SQL
    • Operating on big datasets in Python
    • Data visualization
  • Mathematical optimization
    • Linear optimization concepts
    • Nonlinear continuous optimization
    • Linear algebra
  • Mathematical modeling
    • Using parametrized systems of equations to represent real-world systems
  • Statistics
    • Multivariate regression
    • Clear understanding of Maximum Likelihood estimation and computational methods to find MLE parameters
    • Bayesian concepts
    • Hypotheses testing
Education requirements
Graduate degree in Applied Mathematics, Scientific Computing, Operations Research or related field. We will consider holders of Bachelor degrees with relevant experience
Skills/Aptitude
  • Engineering and detective mindset
    • Both to diagnose data and existing algorithms and to develop new analytics functionality
  • Pragmatic approach to real-world problems
  • Focus on problem solving over applying specific models
  • Willingness to make approximations and assumptions rather than find "the" optimal solution
  • Ability to combine multiple techniques and models to solve end-to end-problems
  • Communication and collaboration skill
  • Ability to convert non-technical requests into project specifications