প্রাইসিং বিশ্লেষক
বিক্রয় ও বিপণনAI এক্সপোজার
- ডেটার উৎস: BLSপ্রকাশকাল: 2026-08
অত্যন্ত উচ্চ· আপেক্ষিক
কমচারটি আপেক্ষিক স্তরঅত্যন্ত উচ্চপেশা-গোষ্ঠী পর্যায়ের মান
স্কেল, ভিত্তি ও উৎস
চারটি আপেক্ষিক স্তর (কম / মাঝারি / উচ্চ / অত্যন্ত উচ্চ)
BLS কর্মসংস্থান পূর্বাভাস সারণির 831টি বিস্তারিত পেশার ভিত্তিতে। মান NEM (ন্যাশনাল এমপ্লয়মেন্ট ম্যাট্রিক্স) কোড অনুযায়ী দেওয়া হয়, তাই একই NEM কোডের পেশাগুলি একই ব্যান্ড পায়
- ডেটার উৎস: Anthropicপ্রকাশকাল: 2026-03
0.220
0.000এখানে থাকা মানগুলোর পরিসর0.745স্কেল, ভিত্তি ও উৎস
- ডেটার উৎস: ILOপ্রকাশকাল: 2025
0.44
0.09এখানে থাকা মানগুলোর পরিসর0.70পেশা-গোষ্ঠী পর্যায়ের মান
স্কেল, ভিত্তি ও উৎস
জেনারেটিভ AI এক্সপোজার সূচক, প্রকাশিত রূপে 0–1
ISCO-08 ইউনিট গ্রুপ — একই কোডের সব পেশা এই মানই পায়
এটি এই সাইটের হিসাব, ILO-এর প্রকাশিত সংখ্যা নয়: এই সাইট ILO ডেটাসেটের সঙ্গে যুক্ত করা ১,০১২টি পেশার মধ্যে 28% এই মানের সমান বা তার বেশি।
এই উৎস কী ধরনের মান প্রকাশ করে
BLS-এর শ্রেণিবিভাগ একটি আপেক্ষিক র্যাঙ্ক, পরম মাত্রা নয়, এবং এটি সরাসরি পরিমাপও নয়: এটি কয়েকটি প্রকাশিত গবেষণায় পাওয়া পেশার পার্সেন্টাইল র্যাঙ্কগুলিকে চারটি স্তরে ভাগ করে। এটি কর্মসংস্থান বা মজুরির পূর্বাভাস নয়, গ্রহণের সম্ভাবনাও নয়, এবং এটি স্বয়ংক্রিয়তা ও সম্প্রসারণের মধ্যে পার্থক্য করে না।
Task-level exposure
শুধু এক্সপোজার থাকা কাজ| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Prepare requirements documentation for use by software developers.13-2099 | 0.080036.4 | 0.020028.6 |
Provide application or analytical support to researchers or traders on issues such as valuations or data.13-2099 | 0.080036.4 | 0.020028.6 |
Define or recommend model specifications or data collection methods.13-2099 | 0.030013.6 | 0.00000.0 |
Interpret results of financial analysis procedures.13-2099 | 0.01004.5 | 0.010014.3 |
Prepare written reports of investigation findings.13-2099 | 0.01004.5 | 0.00000.0 |
Recommend actions in fraud cases.13-2099 | 0.01004.5 | 0.00000.0 |
Evaluate business operations to identify risk areas for fraud.13-2099 | 0.00000.0 | 0.020028.6 |
Produce written summary reports of financial research results.13-2099 | 0.00000.0 | 0.00000.0 |
Apply mathematical or statistical techniques to address practical issues in finance, such as derivative valuation, securities trading, risk management, or financial market regulation.13-2099 | 0.00000.0 | 0.00000.0 |
Gather financial documents related to investigations.13-2099 | 0.00000.0 | 0.00000.0 |
Advise businesses or agencies on ways to improve fraud detection.13-2099 | 0.00000.0 | —0 |
Research new financial products or analytics to determine their usefulness. | —0 | 0.00000.0 |
Create and maintain logs, records, or databases of information about fraudulent activity. | —0 | 0.00000.0 |
| Not observed on any surface — 31 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | ||
Collaborate in the development or testing of new analytical software to ensure compliance with user requirements, specifications, or scope. | —0 | —0 |
Maintain or modify all financial analytic models in use. | —0 | —0 |
Develop core analytical capabilities or model libraries, using advanced statistical, quantitative, or econometric techniques. | —0 | —0 |
Consult traders or other financial industry personnel to determine the need for new or improved analytical applications. | —0 | —0 |
Confer with other financial engineers or analysts on trading strategies, market dynamics, or trading system performance to inform development of quantitative techniques. | —0 | —0 |
Research or develop analytical tools to address issues such as portfolio construction or optimization, performance measurement, attribution, profit and loss measurement, or pricing models. | —0 | —0 |
Devise or apply independent models or tools to help verify results of analytical systems. | —0 | —0 |
Identify, track, or maintain metrics for trading system operations. | —0 | —0 |
Collaborate with product development teams to research, model, validate, or implement quantitative structured solutions for new or expanded markets. | —0 | —0 |
Analyze pricing or risks of carbon trading products. | —0 | —0 |
Assess the potential impact of climate change on business financial issues, such as damage repairs, insurance costs, or potential disruptions of daily activities. | —0 | —0 |
Develop methods of assessing or measuring corporate performance in terms of environmental, social, and governance (ESG) issues. | —0 | —0 |
Develop solutions to help clients hedge carbon exposure or risk. | —0 | —0 |
Develop tools to assess green technologies or green financial products, such as green hedge funds or social responsibility investment funds. | —0 | —0 |
Maintain knowledge of current events and trends in such areas as money laundering and criminal tools and techniques. | —0 | —0 |
Train others in fraud detection and prevention techniques. | —0 | —0 |
Research or evaluate new technologies for use in fraud detection systems. | —0 | —0 |
Prepare evidence for presentation in court. | —0 | —0 |
Negotiate with responsible parties to arrange for recovery of losses due to fraud. | —0 | —0 |
Conduct field surveillance to gather case-related information. | —0 | —0 |
Testify in court regarding investigation findings. | —0 | —0 |
Review reports of suspected fraud to determine need for further investigation. | —0 | —0 |
Lead, or participate in, fraud investigation teams. | —0 | —0 |
Interview witnesses or suspects and take statements. | —0 | —0 |
Design, implement, or maintain fraud detection tools or procedures. | —0 | —0 |
Document all investigative activities. | —0 | —0 |
Coordinate investigative efforts with law enforcement officers and attorneys. | —0 | —0 |
Conduct in-depth investigations of suspicious financial activity, such as suspected money-laundering efforts. | —0 | —0 |
Analyze financial data to detect irregularities in areas such as billing trends, financial relationships, and regulatory compliance procedures. | —0 | —0 |
Obtain and serve subpoenas. | —0 | —0 |
Arrest individuals to be charged with fraud. | —0 | —0 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Prepare requirements documentation for use by software developers.O*NET Task ID 15982 | 1.0 |
Collaborate in the development or testing of new analytical software to ensure compliance with user requirements, specifications, or scope.O*NET Task ID 15985 | 1.0 |
Maintain or modify all financial analytic models in use.O*NET Task ID 15987 | 1.0 |
Produce written summary reports of financial research results.O*NET Task ID 15988 | 1.0 |
Develop core analytical capabilities or model libraries, using advanced statistical, quantitative, or econometric techniques.O*NET Task ID 15990 | 1.0 |
Devise or apply independent models or tools to help verify results of analytical systems.O*NET Task ID 15996 | 1.0 |
Apply mathematical or statistical techniques to address practical issues in finance, such as derivative valuation, securities trading, risk management, or financial market regulation.O*NET Task ID 15997 | 1.0 |
Provide application or analytical support to researchers or traders on issues such as valuations or data.O*NET Task ID 15983 | 0.5 |
Identify, track, or maintain metrics for trading system operations.O*NET Task ID 15984 | 0.5 |
Research new financial products or analytics to determine their usefulness.O*NET Task ID 15986 | 0.5 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page