1

Weekend Python Web Scraping Jobs in California (NOW HIRING)

Data Engineer

San Francisco, CA ยท Remote

$160K/yr

Proficiency in Python and SQL (preferably MySQL) Demonstrated experience with Airflow ... Experience with web scraping and cleaning unstructured data * Knowledge of data science and machine ...

Be a data hunter - Whether it's web scraping, third-party integrations, or unconventional sources ... Technical expertise - You've got Python, SQL, and large-scale data processing tools locked down.

Participate in on-call rotations (limited to your working hours + the occasional weekend) and ... Building large-scale or complex multi-tenant web applications * Parallelization, code optimization ...

Threat Intelligence Engineer

San Francisco, CA ยท On-site +1

$320K - $405K/yr

Have strong coding proficiency in Python and SQL for building detection logic, data pipelines, and ... Familiarity with web scraping and data extraction at scale * Experience with behavioral analytics ...

Senior Engineer

San Francisco, CA ยท On-site

$123K - $169K/yr

Strong general-purpose programming (Python and/or TypeScript), solid SQL/relational databases, and ... web scraping / document extraction, and infrastructure-as-code. We Also Expect You to Have * You ...

Showing results 21-40

Weekend Python Web Scraping information

What is a weekend Python web scraping job?

Weekend Python Web Scraping jobs involve using the Python programming language to collect and extract data from websites, typically during weekend hours or as a part-time remote role. These jobs often require knowledge of web scraping libraries like BeautifulSoup, Scrapy, or Selenium, as well as an understanding of HTML and web protocols. The work can include tasks such as gathering data for market research, competitive analysis, or data aggregation projects. Since the work is scheduled for weekends, it offers flexibility for those who have commitments during the week. Attention to ethical web scraping practices and compliance with website terms of service is usually important.

What are some common challenges faced in a weekend Python web scraping role, and how can they be addressed?

One frequent challenge in weekend Python web scraping roles is dealing with websites that implement anti-scraping measures, such as CAPTCHAs or frequent layout changes. Effective solutions include using libraries like Selenium or Playwright to mimic human browsing, rotating user agents and IP addresses, and staying updated with website structure changes. Additionally, time management is key, as weekend roles often require efficiently balancing multiple scraping tasks within limited hours. Collaborating with other developers or data engineers, even asynchronously, can help share solutions and maintain scraping scripts effectively.

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

To thrive as a Weekend Python Web Scraping Specialist, you need strong proficiency in Python programming, experience with web scraping libraries like BeautifulSoup and Scrapy, and a solid understanding of HTML, CSS, and HTTP protocols. Familiarity with version control systems such as Git, browser automation tools like Selenium, and sometimes cloud platforms is also typically expected. Attention to detail, problem-solving skills, and effective communication are essential soft skills to manage project requirements and address data extraction challenges. These competencies ensure accurate, efficient data gathering and reliable delivery within tight weekend timelines.

What is the difference between Weekend Python Web Scraping vs Weekend Data Analyst?

AspectWeekend Python Web ScrapingWeekend Data Analyst
Required SkillsPython, web scraping libraries, data extractionExcel, SQL, data visualization, basic programming
Work EnvironmentRemote, project-based, technicalRemote or on-site, analytical, business-focused
Industry UsageTech, e-commerce, researchFinance, marketing, consulting

Weekend Python Web Scraping involves writing scripts to extract data from websites, focusing on technical skills like Python programming. Weekend Data Analysts interpret and visualize data to support business decisions, requiring analytical and communication skills. While both roles may work remotely and require some technical knowledge, Python Web Scraping is more technical and coding-intensive, whereas Data Analysis emphasizes data interpretation and reporting.

What are the most commonly searched types of Python Web Scraping jobs in California?

The most popular types of Python Web Scraping jobs in California are:

What job categories do people searching Weekend Python Web Scraping jobs in California look for?

The top searched job categories for Weekend Python Web Scraping jobs in California are:

What cities in California are hiring for Weekend Python Web Scraping jobs?

Cities in California with the most Weekend Python Web Scraping job openings:

Senior AI Engineer, Agentic Data Enrichment

San Francisco, CA โ€ข On-site

$124K - $169K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 21 days ago


Job description

ABOUT BASELAYER


Every business in America needs a bank account to exist. The system that decides whether they're real, who's behind them, and whether they're a risk, runs on infrastructure from the 1980s. We're rebuilding that layer from scratch.

Baselayer is the identity layer for institutions across the United States - the most complete business graph in America and every human tied to it. We fuse public records, IRS data, sanctions lists, web signals, and fraud telemetry from 2,200+ financial institutions into a single graph that resolves any business and the humans behind it in milliseconds. The legacy credit bureaus took 50 years to build something that gets 60% match rates. We've built something that gets 98% in under two years.

Today we're trusted by over 20% of financial institutions in America - including FIS, Rho, Socure and leading loan infrastructure providers. But the graph is becoming infrastructure for anyone who needs to know if a business is real and worth trusting: gig platforms, marketplaces, AI companies, and commerce infrastructure at scale.

Trust is the substrate of every financial transaction. We're rebuilding it.

ABOUT THE TEAM


We're solving real-time entity resolution at a scale no one else has cracked - fusing dozens of data sources into a single business identity graph and resolving any entity in milliseconds. It's a graph AI problem, a retrieval problem, and a fraud-modeling problem stacked on top of each other. The technical depth is real.

You'd be joining a small team where the data moat is defensible, the research problems are open, and the infrastructure you build becomes load-bearing for businesses. Ownership is real. Velocity is real. There's no layer of process between an idea and shipping it.

We're at an inflection point - the graph is built, the match rates speak for themselves, and the hardest problems are still ahead: graph embeddings, fraud propagation models across the business network, real-time traversal at sub-100ms latency, and expanding the identity layer beyond finance into every platform that needs to trust a business.

If you want to work on something foundational - the kind of infrastructure that gets built once and everything else runs on top of - this is it.

ABOUT THE ROLE


Baselayer answers questions the loan application didn't ask. For every business that crosses our queues, we need to know things that aren't on the form: what the business actually does, where it actually lives on the web, whether the people it names match the public record, and whether anything across the open web contradicts the story we were told. We answer those questions with LLM-driven agents that crawl, click, search, and extract structured evidence from across the web - and we treat this as a production data pipeline, not a research demo. We're hiring a Senior AI Engineer to own a slice of this enrichment surface end-to-end.

WHAT YOU'LL DO


  • Own industry/category classification of businesses from heterogeneous signals (name, website, directory presence, reviews).
  • Build and maintain discovery and verification systems for a business's real web presence - filtering aggregators, parked domains, brand collisions, and impersonators.
  • Link individuals to businesses via public web evidence (e.g. confirming a named officer or employee genuinely works there).
  • Develop risk/legitimacy scoring derived from web-presence signals, fed back into downstream underwriting.
  • Build and evolve the shared agent infrastructure: provider-agnostic base agents, shared toolset registry (browser navigation, search, scraping, structured database lookups, scoring), eval harness, and instrumentation surface for token-and-tool tracing.
  • Own model selection, agent design, prompt and tool engineering, eval methodology, and cost control across your enrichment surface.

MINIMUM REQUIREMENTS


  • Shipped LLM-driven agents to production - not notebooks, not demos. Real users, real cost, real failure modes, real on-call.
  • Strong async Python including structured-data libraries, modern web frameworks, and relational databases.
  • Experience across multiple frontier LLM providers and at least one agent framework, with deep knowledge of failure modes.
  • Built or maintained eval methodology: curated golden datasets, scoring functions, labelling guidelines, regression diagnostics.
  • Browser automation experience: headless browsers, anti-bot evasion, authenticated flows.
  • Holds informed opinions on structured-output reliability - when to use JSON-schema mode vs. function calling vs. extractor-on-top-of-text.

WHAT SETS YOU APART


  • Web scraping at scale: anti-bot evasion, residential proxies, request fingerprinting, authenticated flows, CDN defeats.
  • Eval-framework experience (e.g., LangSmith, Braintrust, Evals, or custom).
  • Entity resolution / record linkage / fuzzy matching at scale.
  • Browser-automation experience at the devtools-protocol level.
  • Built a tool registry or toolset abstraction over multiple LLM providers.
  • Cost/latency optimization: response caching, semantic caching, model routing (cheap-first then escalate), thinking-budget tuning, prompt-cache hit-rate work.

WORK LOCATION


  • Based in SF; hybrid - 4 days per week in office.

COMPENSATION


  • Salary Range: $230,000 - $340,000 + Equity

BENEFITS


  • Time off when you need it: Flexible PTO so you can recharge without red tape.
  • In-person energy: We're based in SF and meet in the office 4 days a week.
  • Competitive compensation: We pay well and back it with equity. We want you to think and act like an owner.
  • Career rocket fuel: You'll help build the foundation of a high-growth startup, working side by side with experienced founders and team members who've done it before.
  • Benefits on us: We cover 100% of your health, dental, and vision premiums. No surprise deductions from your paycheck.
  • 401(k) with company match: We match your contributions so your future self benefits too
  • HSA contributions included: We contribute to your HSA on applicable plans, so your coverage works as hard as you do
  • Stay healthy, stay sharp: A $250 monthly gym stipend to help you bring your best self to work, and everywhere else
  • A seat at the table: We believe in transparency, radical candor, and giving every team member a voice