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Remote Machine Learning Jobs in Frisco, TX (NOW HIRING)

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... The Opportunity As a Senior Data Scientist, you will leverage advanced analytics, machine learning ...

Senior ITSMA Observability Engineer

Dallas, TX · On-site +1

$103K - $142K/yr

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... HedgeServ supports employees through a variety of offerings, including remote and hybrid working ...

Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ... Candidate can live anywhere in the United States. #LI-MP2 #LI-REMOTE Basic Requirements * 8+ years ...

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Remote Machine Learning information

See Frisco, TX salary details

$23.9K

$39.9K

$82.4K

How much do remote machine learning jobs pay per year?

As of Jul 18, 2026, the average yearly pay for remote machine learning in Frisco, TX is $39,855.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,400.00 and $43,100.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Engineer, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
What are the most commonly searched types of Machine Learning jobs in Frisco, TX? The most popular types of Machine Learning jobs in Frisco, TX are:
What are popular job titles related to Remote Machine Learning jobs in Frisco, TX? For Remote Machine Learning jobs in Frisco, TX, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning jobs in Frisco, TX look for? The top searched job categories for Remote Machine Learning jobs in Frisco, TX are:
What cities near Frisco, TX are hiring for Remote Machine Learning jobs? Cities near Frisco, TX with the most Remote Machine Learning job openings:
Infographic showing various Remote Machine Learning job openings in Frisco, TX as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $39,855 per year, or $19.2 per hour.
Senior Data Scientist - Operation Research

Senior Data Scientist - Operation Research

Tiger Analytics Inc.

Dallas, TX • On-site, Remote

Full-time

Posted 24 days ago


Job description

Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce.

We are also market leaders in AI and analytics consulting in the CPG & retail industry with over 40% of our revenues coming from the sector. This is our fastest-growing sector, and we are beefing up our talent in the space.

We are looking for a Senior Data Scientist with a good blend of data analytics background, practical experience in Operation research strategies and Pricing Analytics within supply chains, and strong coding capabilities to add to our team.

Key Responsibilities:

  • Responsible for refactoring the Optimization algorithm written in Python using Object Oriented Programming
  • Work on the latest applications of data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG.
  • Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to Pricing Optimization.
  • Develop and implement predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource allocation across the supply chain.
  • Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
  • Design and execute experiments to evaluate the effectiveness of different replenishment strategies and allocation policies.
  • Monitor and analyze key performance indicators (KPIs) related to replenishment and supply chain allocation, and provide recommendations for continuous improvement.
  • Stay abreast of industry trends and best practices in data science, replenishment optimization, and supply chain management, and leverage this knowledge to drive innovation within the organization.
  • Collaborate, coach, and learn with a growing team of experienced Data Scientists.

Requirements

  • Proven experience 6+ years working as a Data Scientist, with a focus on supply chain optimization and inventory allocation.
  • MS or PhD in Computer Science, Operations Research, Applied Mathematics, Machine Learning, or a related field.
  • Experience with using mathematical programming solvers such as Gurobi, Xpress MP, CPLEX, or Google OR Tools in applications.
  • Experience with MLflow and model lifecycle management
  • Experience building end-to-end ML pipelines in production
  • Solid understanding of statistical methods, optimization techniques, and predictive modelling concepts.
  • Strong proficiency in programming languages such as Python, Pyspark and SQL, and experience working with data analysis and machine learning libraries.
  • Ability to apply various analytical models to business use cases
  • Exceptional communication and collaboration skills to understand business partner needs and deliver solutions and explain to business stakeholders.

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.