Drilling Data Analyst

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule as needed. Must not repeat job title. Must not include Job ID etc. Must preserve all substantive info, remove boilerplate (EEO, legal, etc). Must include sections only if posting has real specific content. Let's parse the posting: - Role: Drilling Data Analyst (title not needed) - Location: Houston, TX 77040 - Duration: 6-12 Month Contract - Work Authorization: US Citizen, Green Card, or Authorized to Work in the US - NOTE: This is an onsite position Description: paragraphs about team, projects, role responsibilities. Detailed Description: bullet-like sentences. Job Requirements: list of abilities. Minimum Qualifications: bullet list. Preferred Qualifications: bullet list. About INSPYR Solutions: company description (maybe not needed? It's boilerplate? It's about the company, but not required? The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The "About INSPYR Solutions" is not EEO but it's company description; might be considered substantive? It's not about the role. Probably we can drop it as it's not directly about the job. The instruction: "Preserve ALL substantive information; do NOT invent or summarize away detail." The company description may be considered not substantive for the job? It's ambiguous. Usually we keep only job-related content. The "About INSPYR Solutions" is generic fluff; could be considered boilerplate. Safer to omit. EEO etc must be removed. Thus we need sections: - About the role: could combine description paragraphs. - Responsibilities: from description and detailed description. - Requirements: from Job Requirements. - Qualifications: Minimum Qualifications (maybe separate section "Qualifications"). - Skills: maybe combine Python, Power BI, SQL etc? Could be part of Requirements. - Benefits, Pay, Schedule: not provided, so omit. We must not create empty sections. Thus produce sections: About the role, Responsibilities, Requirements, Qualifications, Skills. Check if we have content for each. About the role: we can use the initial description paragraphs (the first paragraph after Description). That includes: "The Data Science and Analytics team is a growing group..." etc. That's substantive. Responsibilities: from "The Drilling Data Analyst will help build..." and "The candidate will be involved..." and Detailed Description bullet points. Requirements: from Job Requirements list. Qualifications: from Minimum Qualifications (maybe also Preferred Qualifications could be under Qualifications as "Preferred" but we can include both under Qualifications with subheadings? Not allowed to create extra headings beyond specified list. Could put both minimum and preferred under Qualifications as a list, distinguishing with text. That's okay. Skills: maybe we can extract specific skills: Python, Power BI, SQL, data analysis, communication, etc. Could be a separate section. But we must avoid duplication. If we put skills in Qualifications, we may not need separate Skills section. However we have a list of skills in Requirements and Qualifications; we could combine them into Skills section. But we already have Requirements section for abilities; Qualifications for education/experience. Skills could be technical skills. Let's decide: - About the role: description paragraph. - Responsibilities: list of duties (the Drilling Data Analyst will help..., The candidate will be involved..., Detailed Description points). - Requirements: list of abilities (Job Requirements). - Qualifications: education and experience (Minimum and Preferred). - Skills: maybe not needed if we covered in Requirements. But we could still have Skills for technical tools: Python, Power BI, SQL, Jupyter Notebooks, Pandas, Matplotlib, etc. However those are already in Minimum Qualifications. Might be redundant. Given instruction: "Prefer a few substantive sections over many thin ones." So maybe we combine Requirements and Skills into one section? But we have headings list; we can choose to include only those with real content. Could include About the role, Responsibilities, Requirements, Qualifications. That's four sections. That seems sufficient. We must not repeat job title. Use

for each section heading. Inside sections, use

for prose,

• for lists. We need to preserve all substantive info: location, duration, work authorization, onsite note. Where to put? Could be in About the role as a short paragraph at start. Or we could add a small

  with metadata. The instruction: "Do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

  or drop it." So we can include location, duration, work authorization, onsite in a short

  under About the role or maybe a separate meta paragraph before sections. Probably best to include after the heading About the role a short paragraph with location, duration, work authorization, onsite. Let's craft:

  About the role

  Location: Houston, TX 77040. Duration: 6‑12 month contract. Work authorization: US Citizen, Green Card, or authorized to work in the US. This is an onsite position.

  [description paragraph...]

  Then Responsibilities
  with items. Requirements
  with items. Qualifications
  with items (minimum and preferred). Could separate with text like "Minimum:" and "Preferred:" inside
  • ? Better to have separate
    for each? But we can't have multiple headings same name. Could include a

    stating "Minimum qualifications:" then list, then "Preferred qualifications:" then list. That's okay. Let's extract details. Description paragraph(s): "The Data Science and Analytics team is a growing group of energetic, passionate individuals working to improve and inform the organization through data. We work primarily with the drilling automation team to help design, evaluate, and improve novel drilling automation technology. Some example projects that we are applying analytics and data science to include: Modeling greenhouse gas emissions from the rig fleet to reduce environmental impact and improve reporting; Generate analyses over drilling advisory systems to improve drilling efficiency and product utilization; Developing automated monitoring, detection, and alerting of operational events." That's one paragraph with semicolons. We'll keep as prose. Then: "The Drilling Data Analyst will help build next-generation drilling systems by: Analyzing data to forward our understanding of various drilling phenomena; Creating and automating insightful reports that support commercialization and utilization; Providing quality control checks against new and existing products; Working directly with the product development team to understand key needs." Then: "The candidate will be involved in all aspects of the project life cycle, including working directly with stakeholders, cleaning and analyzing data, generating and presenting visuals and reports, and providing quality control and support of commercial products." Then: "The ideal candidate would be a collaborator, possess advanced data analytics skills, be expert in working with large data sets in Python, and be able to communicate clearly with numerous stakeholders. This role is designed for early career candidates with an emphasis on training and development and performs under the general direction of a Lead Data Scientist." Then Detailed Description bullet points (converted to sentences): - Execute in parallel multiple analytics projects of varying complexity and data sources (~1 week to ~3 months) - Quickly learn aspects of the drilling process and equipment to efficiently derive insights from our data - Independently manage and execute above projects from start-to-finish, including understanding stakeholder needs; acquiring necessary data; cleaning / analyzing data and innovating beyond initial requirements; generating visuals / reports; and presenting results to stakeholders - Provide quality control and sustainment work to existing products by finding and addressing issues Job Requirements list: - Able to quickly learn the details of oil and gas drilling to better analyze our data - Able to analyze data efficiently and accurately by utilizing Python and Power BI - Able to work both independently and as part of a team, managing multiple tasks and projects simultaneously to meet challenging deadlines - Able to visit operating rigs on short-duration trips to become familiar will drilling operations (typo "will" but keep) - Able to think strategically and translate concepts into action plans and track results - Comfortable explaining complex analytics concepts and results to end-users - Excellent verbal and written English language communication Minimum Qualifications: - A bachelor's degree in engineering, physics or related field - 2 years of experience with Python for data analysis (such as Jupyter Notebooks, Pandas, Matplotlib) - 2 years of experience using Power BI for data visualization - 2 years of experience using SQL for data extractions Preferred Qualifications: - A master's degree in engineering, Physics, or related field - 2 years of experience in the oil and gas industry - 1 year of experience working in cross-functional roles and communicating directly with product users, customers, or other stakeholders Now produce HTML. We'll wrap each section in

    then content. For About the role: include meta paragraph then description paragraph(s). Could combine into multiple

    . Let's produce:

    About the role

    Location: Houston, TX 77040. Duration: 6‑12 month contract. Work authorization: US Citizen, Green Card, or authorized to work in the US. This is an onsite position.

    The Data Science and Analytics team is a growing group of energetic, passionate individuals working to improve and inform the organization through data. We work primarily with the drilling automation team to help design, evaluate, and improve novel drilling automation technology. Some example projects that we are applying analytics and data science to include: Modeling greenhouse gas emissions from the rig fleet to reduce environmental impact and improve reporting; Generate analyses over drilling advisory systems to improve drilling efficiency and product utilization; Developing automated monitoring, detection, and alerting of operational events.

    The Drilling Data Analyst will help build next-generation drilling systems by: Analyzing data to forward our understanding of various drilling phenomena; Creating and automating insightful reports that support commercialization and utilization; Providing quality control checks against new and existing products; Working directly with the product development team to understand key needs.

    The candidate will be involved in all aspects of the project life cycle, including working directly with stakeholders, cleaning and analyzing data, generating and presenting visuals and reports, and providing quality control and support of commercial products.

    The ideal candidate would be a collaborator, possess advanced data analytics skills, be expert in working with large data sets in Python, and be able to communicate clearly with numerous stakeholders. This role is designed for early career candidates with an emphasis on training and development and performs under the general direction of a Lead Data Scientist.

    Then Responsibilities

    Responsibilities

    with items from Drilling Data Analyst will help..., candidate involved..., Detailed Description points. Let's list: - Analyzing data to forward our understanding of various drilling phenomena - Creating and automating insightful reports that support commercialization and utilization - Providing quality control checks against new and existing products - Working directly with the product development team to understand key needs - Working directly with stakeholders, cleaning and analyzing data, generating and presenting visuals and reports, and providing quality control and support of commercial products - Execute in parallel multiple analytics projects of varying complexity and data sources (~1 week to ~3 months) - Quickly learn aspects of the drilling process and equipment to efficiently derive insights from our data - Independently manage and execute above projects from start-to-finish, including understanding stakeholder needs; acquiring necessary data; cleaning / analyzing data and innovating beyond initial requirements; generating visuals / reports; and presenting results to stakeholders - Provide quality control and sustainment work to existing products by finding and addressing issues We could combine some but fine. Requirements

    Requirements

    list. Qualifications

    Qualifications

    we can have two paragraphs: Minimum qualifications and Preferred qualifications each followed by
    . Let's do:

    Minimum qualifications:

    ...

    Preferred qualifications: