CS代考计算机代写 algorithm Economics 691-06: Final Project

Economics 691-06: Final Project
Due by email to nshah13@usfca.edu by 11:59pm PT on Wednesday, October 14. Please put ¡°Final Project¡± in the title of the email.
Instructions
Please write a memo per the prompt below. Note that there is no collaboration, and there are no late submissions permitted. I will also not be able to answer any questions about the final project, outside of simple logistical questions or clarifying questions. Finally, limit your answer to 2,000 words, and include a word count at the end. References are not necessary; but if included, they do not count towards the word limit.
Background and Prompt
Consider the hypothetical start-up firm Careerist, which is oriented around helping firms hire grad- uates from community colleges, vocational schools, and other non-four year colleges across the United States. Careerist operates a two-sided platform: companies can post job openings on their site to which graduates can apply, and similarly graduates can post their resumes on the site and companies can reach them. Careerist¡¯s primary business model is to charge companies a fee for every hire they successfully make through the platform. Careerist offers two ancillary services: it has a service called ResumeReview, in which a human reviews the resumes of graduates and makes suggestions; and it has a service called SmartMatch, in which an algorithm helps companies iden- tify promising candidates for their job postings. Careerist charges a small fee for ResumeReview to cover the costs of a reviewer¡¯s time, and does not charge for SmartMatch at all. In both cases, Careerist does not view these as direct revenue generators; but instead believes that better resumes and more relevant applicant pools will translate into more hires.
In terms of the approximate numbers, Careerist has several hundred firms and tens of thousands of graduates registered on the site. All firms have posted at least one job opening; and a few hundred firms have also contacted graduates directly, either on their own initiative or after using SmartMatch. All graduates have posted resumes on the site, although only a small fraction have used ResumeReview to improve their resumes. Around half the graduates have applied for at least one job, either after browsing the open listings or after being contacted directly by companies. Careerist has facilitated a few thousand matches thus far.
These usage numbers are growing quickly, and Careerist raised a lot of money from venture capital firms accordingly. Given the product growth and the fresh funding, they hired you as their first data scientist. You report to the CEO, who has a technical background and is familiar with basic statistics; but she is not a data scientist herself. She asks you for a memo, in which you recommend three specific experiments or analyses for the firm to run. For each of the three experiments, she asks you to describe both what Careerist would learn from the experiment and how Careerist might implement the experiment. She also asks you to be clear about the tradeoffs or limitations for any method you propose.
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Evaluation
The memo will be scored based on four principles.
1. Technical Accuracy: Does the memo accurately describe the experimental analyses it pro- poses, both in implementation and in its advantages and disadvantages?
2. Readability: Is the memo readable to someone who is not a domain expert but is instead focused on the big picture; and does it do a good job advocating for its proposed experiments?
3. Honesty: Does the memo thoughtfully reflect the tradeoffs, limitations, or downsides for the experiments it proposes and the choices it made?
4. Creativity: Is the memo sufficiently creative in the experiments it designs and recommends, given the business model of Careerist?
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