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Python Scraping Jobs in Texas (NOW HIRING)

... R, Python, or other scripting languages. They are comfortable working with APIs, web scraping, and SQL/no-SQL databases. They automate business workflows while integrating stochastic/numeric ...

... R, Python, or other scripting languages. They are comfortable working with APIs, web scraping, and SQL/no-SQL databases. They automate business workflows while integrating stochastic/numeric ...

... R, Python, or other scripting languages. They are comfortable working with APIs, web scraping, and SQL/no-SQL databases. They automate business workflows while integrating stochastic/numeric ...

Data Specialist

Houston, TX · On-site

$47K/yr

Python, R, SQL, Stata, Tableau, Power BI, or similar tools. Data normalization, records linkage, fuzzy matching, probabilistic matching, or deduplication. OCR, PDF extraction, web scraping, text ...

Data Specialist

Houston, TX · On-site

$47K/yr

Python, R, SQL, Stata, Tableau, Power BI, or similar tools. Data normalization, records linkage, fuzzy matching, probabilistic matching, or deduplication. OCR, PDF extraction, web scraping, text ...

Showing results 41-52

Python Scraping information

See Texas salary details

$12

$54

$80

How much do python scraping jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for python scraping in Texas is $54.61, according to ZipRecruiter salary data. Most workers in this role earn between $45.00 and $62.02 per hour, depending on experience, location, and employer.

What is Python scraping?

Python scraping refers to the process of using the Python programming language to extract data from websites or online sources. It typically involves sending HTTP requests to webpages, parsing the HTML or other content, and collecting specific information for analysis or storage. Popular Python libraries for web scraping include BeautifulSoup, Scrapy, and Requests. This technique is widely used in data analysis, research, and business intelligence, but it's important to respect website terms of service and legal guidelines when scraping data.

What are the key skills and qualifications needed to thrive as a Python scraping specialist, and why are they important?

To thrive as a Python Scraping Specialist, you need strong proficiency in Python programming, understanding of web protocols (HTTP, HTML, CSS), and experience with libraries such as BeautifulSoup, Scrapy, or Selenium. Familiarity with version control systems like Git and knowledge of data storage formats (JSON, CSV, SQL) are also commonly required. Problem-solving, attention to detail, and effective communication are valuable soft skills in this role. These skills ensure efficient data extraction, compliance with website policies, and the ability to deliver actionable insights from web data.

What are some common challenges faced by Python scraping professionals, and how can they be addressed?

Python Scraping professionals often encounter obstacles such as website anti-scraping measures, dynamic content loading with JavaScript, and frequent changes in website structures. Overcoming these challenges typically involves using tools like Selenium or Playwright for dynamic pages, rotating proxies and user agents to avoid detection, and writing adaptable, modular code to quickly update scrapers when site layouts change. Staying up to date with the latest libraries and best practices is vital for efficiency and compliance with legal and ethical standards.

What is the difference between Python Scraping vs Data Analyst?

AspectPython ScrapingData Analyst
Required SkillsPython programming, web scraping libraries (BeautifulSoup, Scrapy)Data analysis, SQL, Excel, statistical skills
Work EnvironmentTechnical, coding-focused, often remoteBusiness-focused, reporting, presentations
Industry UsageWeb data extraction, research projectsBusiness insights, decision-making
CertificationsPython certifications, web scraping coursesData analysis certifications (e.g., CAP, Microsoft Certified)

Python Scraping involves writing code to extract data from websites, focusing on programming skills and technical tools. Data Analysts interpret and visualize data for business insights, requiring analytical and statistical skills. While both roles work with data, Python Scraping is more technical and coding-intensive, whereas Data Analysts focus on analyzing and presenting data for decision-making.

Infographic showing various Python Scraping job openings in Texas as of August 2026, with employment types broken down into 1% Internship, 88% Full Time, 6% Part Time, and 5% Contract. Highlights an 76% Physical, 7% Hybrid, and 17% Remote job distribution, with an average salary of $113,599 per year, or $54.6 per hour.

Manager of Data Science

Austin, TX • On-site

Cliftonlarsonallen
Accounting Services • 5 - 10K employees

Full-time

Medical, Dental, Vision, Retirement

Posted 9 days ago


CliftonLarsonAllen rating

7.1

Company rating: 7.1 out of 10

Based on 30 frontline employees who took The Breakroom Quiz

22nd of 23 rated bookkeepers and accountants


Job description

CLA is a top 10 national professional services firm where our purpose is to create opportunities every day, for our clients, our people, and our communities through industry-focused wealth advisory, digital, audit, tax, consulting, and outsourcing services. Even with more than 8,500 people, 130 U.S. locations, and a global reach, we promise to know you and help you.

CLA is dedicated to building a culture that invites different beliefs and perspectives to the table, so we can truly know and help our clients, communities, and each other.

CLA is looking to hire a Data Science Director to join our growing Internal IT team.

About the role:

CLA is looking to hire a Manger of Data Science

This role constructs complex solutions that integrate data wrangling, visualization, and advanced modeling techniques into a seamless workflow using software development best practices in R, Python, or other scripting languages. They are comfortable working with APIs, web scraping, and SQL/no-SQL databases. They automate business workflows while integrating stochastic/numeric algorithms in the process. This role will develop more autonomy to develop solutions and will lead others, take on administrative tasks, perform support roles, and get involved in new business development.

As Manager of Data Science, you will have to following responsibilities:

Leadership

  • Provide daytoday leadership, coaching, development, and performance management.

  • Mentor and guide analysts, supporting onboarding, skill development, and continuous learning across career stages.

  • Conduct workload planning, prioritization, and resource allocation to support multiple concurrent initiatives.

  • Build and sustain a highperforming team culture rooted in collaboration, quality, accountability, and innovation.

Technical Oversight

  • Lead and oversee large scale analytical and AI initiatives, including data acquisition, transformation, modeling, AI system development, automation, and insight generation.

  • Provide technical oversight and review of analytical approaches, models, and AI systems to ensure sound methodology, reproducibility, and scientific rigor.

  • Guide the development and application of advanced statistical, machine learning, and AI-driven solutions, including predictive models, computer vision, large language models (LLMs), and agent-based systems.

  • Lead the design and oversight of AI-enabled systems, including prompt engineering strategies, retrieval-augmented generation (RAG), embeddings, and agentic workflows.

  • Establish and evolve analytical and AI best practices, documentation standards, and technical frameworks across the team.

  • Ensure standards for model and AI system validation, monitoring, evaluation, documentation, and responsible AI use are consistently applied.

  • Partner with engineering, IT, and data platform teams to enable scalable, reliable, and well governed solutions.

Workflow Management

  • Own delivery outcomes for data science and AI workstreams, ensuring solutions meet quality, performance, and business expectations.

  • Translate business objectives into clear analytical and AI priorities, balancing near term delivery with long term capability building.

  • Oversee planning, prioritization, and resourcing across projects and teams.

  • Monitor solution performance, validation results, and model or AI system stability; guide troubleshooting of complex data, model, or AI issues.

  • Ensure solutions are productionized effectively, with clear ownership, monitoring, and integration into business workflows.

  • Establish, refine, and enforce standards for documentation, reproducibility, quality assurance, and governance.

  • Remove obstacles, manage risks, and ensure consistent execution across initiatives.

CrossFunctional Collaboration

  • Serve as a primary point of contact for business and functional leaders on analytics and AI initiatives.

  • Partner with stakeholders to define business questions, success metrics, analytical frameworks, and delivery expectations.

  • Coordinate work across teams, offices, and disciplines to ensure alignment of analytical and AI approaches and outcomes.

  • Communicate progress, risks, and results clearly to both technical and non technical audiences.

  • Evaluate and recommend adoption of new data sources, technologies, and analytical and AI tools.

  • Contribute to enterprise level analytics and AI strategy, including identifying high impact use cases and guiding their transition from concept to production.

What you will need:

8 years of relevant experience required.

  • Experience in data analytics, statistics, data science, AI, financial consulting, computer science or related field required.

  • Experience with APIs, web scraping, SQL/no-SQL databases, and cloud-based data solutions required.

  • Supervisory experience required.

Education

Bachelor's degree is required. Combination of relevant experience, education, and training may be accepted in lieu of degree.

  • Degree in Statistics, Computer Science, Economics, Analytics, Data Science (e.g., Informatics, Data Science, Health Data Science), AI, or related field preferred.

  • Masters in a Data Science/Analytics/AI is a plus

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Wellness at CLA

To support our CLA family members, we focus on their physical, financial, social, and emotional well-being and offer comprehensive benefit options that include health, dental, vision, 401k and much more.


To view a complete list of benefits, click here.



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About CliftonLarsonAllen

Sourced by ZipRecruiter

CliftonLarsonAllen (CLA) is a leading professional services company based in Minneapolis, MN, US. CLA operates in the accounting industry and offers a broad range of products and services such as wealth advisory, outsourcing, audit, tax, and consulting services. The company was founded in 1953 with a merger between two firms, Clifton Gunderson and LarsonAllen, in 2012. Working in accordance with their mission to create opportunities for clients, people, and communities, they have established a presence across the US, serving privately held businesses, non-profits, and governmental entities. Recognized for their contributions, CLA has received accolades such as the Innovative Firm of the Year award.

Industry

Accounting services

Company size

5,001 - 10,000 Employees

Headquarters location

Minneapolis, MN, US

Year founded

2012