sentence-transformers How to use Fe2x/distilroberta-ai-job-embeddings with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Fe2x/distilroberta-ai-job-embeddings")
sentences = [
"Data Scientist for Employee Engagement, statistical methods, user classification models",
"Experience : 8 to 10 Years Job Description:Mandatry Skill: AWS ,python\nknowledge To ensure successful initiation, planning, execution, control and completion of the project by guiding team members on technical aspects, conducting reviews of technical documents and artefacts.Lead project development, production support and maintenance activities.Fill and ensure timesheets are completed, as is the invoicing process, on or before the deadline. Lead the customer interface for the project on an everyday basis, proactively addressing any issues before they are escalated. Create functional and technical specification documents. Track open tickets/ incidents in queue and allocate tickets to resources and ensure that the tickets are closed within the deadlines.Ensure analysts adhere to SLA/KPI/OLA. Ensure that all in the delivery team, including self, are constantly thinking of ways to do things faster, better or in a more economic manner. Lead and ensure project is in compliance with Software Quality Processes and within timelines. Review functional and technical specification documents. Serve as the single point of contact for the team to the project stakeholders.Promote team work, motivate, mentor and develop subordinates. Provide application production support as per process/RACI (Responsible, Accountable, Consulted and Informed) Matrix.",
"Experience: 1-5 years of overall work history experience with 1 of those year being company-based IT experience. is a plus-or 1 year of IT company related experience or 2 years of all IT related experience\nTechnical Experience (must haves): Python, Java or C# or C++ (one or the other) More than one isa plus with also SQL and Linux – Good for resumes to have Linux on them. Must know how to code in one of these coding languages: Python, Java, C#, C++, Scala\nEducation: MUST have a bachelor’s or master’s degree in data science, Statistical Computing, Mathematical Statistics, Mathematics, Computer Science: Software Engineering, Information Systems:Software Engineering, SoftwareDevelopment, Information Technology: Programming and Software Development, Computer Science, Computer Systems Engineering, Industrial Engineering, if it’s a non-related IT degree outside of IT, they must have an Associates within IT. Physic degrees would be case by case based on the actual roles they have had since graduation. Relevant roles for BD would pass them with those degree",
"experience at Amazon, driving productivity and retention, and resulting in a motivated workforce of over 1.5 million associates and corporate employees. These are the questions we ask — Are we facilitating the right conversations to build an engaged workforce? What trends are we seeing in our employee data and what should managers do about it? How do we solve customer problems in the most efficient way possible? If these challenges sound interesting to you, you want to be a part of building ‘first of their kind’ products, and you are passionate about putting employee experience first, consider the PeopleInsight team. PI helps Amazon drive improvements in employee talent outcomes (e.g., job satisfaction and retention), and strive to be Earth’s Best Employer through scalable technology.\n\nPI is looking for a customer-obsessed Data Scientist for Employee Engagement Services, a suite of internal employee engagement and recognition products supporting Amazonians WW, with a strong track record of delivering results and proven research experience. This role will own and execute strategic cross-functional employee engagement experiments, analysis and research initiatives across Operations and Corporate audiences for high CSAT products. The Data Scientist must love extracting, cleaning and transforming high volume of data into actionable business information and be able to drive actionable insights. The data scientist will partner with Product, UX and Dev teams to own end-to-end business problems and metrics with a direct impact on employee experience. Success in this role will include influencing within your team and mentoring peers. The problems you will consider will be difficult to solve and often require a range of data science methodologies combined with subject matter expertise. You will need to be capable of gathering and using complex data set across domains. You will deliver artifacts on medium size projects, define the methodology, and own the analysis. Your findings will affect important business decisions. Solutions are testable and reproducible. You will create documents and share findings in line with scientific best practices for both technical and nontechnical audiences.\n\nKey job responsibilities\n\n Implement statistical methods to solve specific business problems utilizing code (Python, R, Scala, etc.). Drive design and development of user classification models and other predictive models to enable a personalized experience for a user. Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters. Collaborate with product management, software developers, data engineering, and business leaders to define product requirements, provide analytical support, and communicate feedback; develop, test and deploy a wide range of statistical, econometric, and machine learning models. Build customer-facing reporting tools to provide insights and metrics which track model performance and explain variance. Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our solutions, as well as sharing insights and recommendations. Earn the trust of your customers by continuing to constantly obsess over their needs and helping them solve their problems by leveraging technology\n\nAbout The Team\n\nThe PeopleInsight team is a collaborative group of Business Intelligence Engineers, Data Scientists, Data Engineers, Research Scientists, Product Managers, Software Development Engineers, Designers and Researchers that studies a workforce numbering in the hundreds of thousands. Our work is dedicated to empowering leaders and enabling action through data and science to improve the workplace experience of associates and ensure Amazon is Earth's Best Employer.\n\nWe are open to hiring candidates to work out of one of the following locations:\n\nSeattle, WA, USA\n\nBasic Qualifications\n\n 2+ years of data scientist experience 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience Experience applying theoretical models in an applied environment\n\nPreferred Qualifications\n\n Experience in Python, Perl, or another scripting language Experience in a ML or data scientist role with a large technology company\n\nAmazon is committed to a diverse and inclusive workplace. Amazon is \n\nOur compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $111,600/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.\n\n\n\nCompany - Amazon.com Services LLC\n\nJob ID: A2605420"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
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