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wdss-price-crossover-project.html
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<!doctype html>
<html class="no-js" lang="zxx">
<head>
<meta charset="utf-8">
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<title>WDSS: Price Crossover Project | WDSS Recruitment</title>
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<h2>WDSS: Price Crossover Project</h2>
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<h4>Price Crossover Project</h4>
<ul>
<li>WDSS</li>
<li><i class="fas fa-map-marker-alt"></i>Coventry, UK (Remote)</li>
<li>Temporary</li>
</ul>
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<p>Take part in this Summer Research Project ran by WDSS, building essential team-working experience and supercharging your CV with real-world experience.
More details about the Summer Research Projects scheme can be found on our <a href="https://research.wdss.io/summer-research-projects/"> info website</a>. </p>
<p>The final product will be published on WDSS's <a href="https://research.wdss.io/">research blog</a>.</p>
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<h4>Difficulty: ★ ★ ★ ☆ ☆</h4>
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<h4>Project Overview</h4>
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<p>Utilise Data Science skills to find the best opportunities on the stock market with the <a href = https://www.investopedia.com/articles/active-trading/052014/how-use-moving-average-buy-stocks.asp></a>crossover strategy.</p>
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<h4>Objectives</h4>
</div>
<ul>
<li>Create a web app that collects current and past price data of the S&P 500 stocks an applies the crossover strategy</li>
<li>Create a rating algorithm that will assess the Crossover strategy results and pick the five stocks that scores the best. (Rating algorithm should pick stocks whose moving averages are crossing or are likely to cross soon.)</li>
</ul>
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<h4>Role Responsibilities</h4>
</div>
<b>Economics expert</b>
<ul>
<li>Guide the data collection process</li>
<li>Help with the design of the rating algorithm</li>
<li>Assess the pros and cons of the crossover strategy</li>
<li>Contribute to the relevant sections of the final write-up</li>
</ul>
<b>Data Engineer</b>
<ul>
<li>Collect the data about stock prices and try to automatise the process</li>
<li>Perform data cleaning and engineering to prepare the dataset</li>
<li>Help with the design of the rating algorithm</li>
<li>Contribute to the relevant sections of the final write-up</li>
</ul>
<b>Data Scientist</b>
<ul>
<li>Design and implement the rating algorithm using the crossover strategy</li>
<li>Create the web-app with interactive visualisation of the stock prices and the price crossover</li>
<li>Contribute to the relevant sections of the final write-up</li>
</ul>
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<h4>Candidate Attributes</h4>
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<ul>
<li>A passion for the project and, preferably, interdisciplinary data science in general</li>
<li>Self-starting attitude with willingness to research and problem-solve independently</li>
<li>Ability to work well in a team and clearly communicate your ideas</li>
<li>Strong time-management and organisational skills.</li>
<li>For the role of Data Engineer and Data Scientist intermediate Python are desired. Familiarity with R is a plus.</li>
</ul>
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<h4>How to Apply</h4>
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<ul>
<li>Use the application button on this page to fill in the form where you should attach your CV and any other sources you think are relevant for the role (e.g. GitHub profile for a coding role)
as well as answering two further questions in which you should demonstrate your motivation and suitbility for the project.</li>
<li>Results to be announced by the end of term 3 (Saturday 3 July 2021)</li>
<li>You <b>can</b> apply for more than one project</li>
</ul>
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<h4>Job Overview</h4>
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<ul>
<li>Location : <span>Coventry, UK (Remote)</span></li>
<li>Start date : <span>05 July 2021</span></li>
<li>Application start : <span>15 May 2021</span></li>
<li>Application end : <span>25 June 2021</span></li>
</ul>
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<a href="https://forms.gle/eVP9hmBdU5wmxU8g6" target ="_blank" class="btn">Application form</a>
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You can find the full application details in the job listing.
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<h4>About WDSS</h4>
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<p>WDSS is a student-led society focused on spreading the word of interdisiplinary data science through talks, networking, teaching, and research.</p>
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