Intern, Data Science

<div class="content-intro"><p></p> <div> <p><span style="color: rgb(124, 146, 248);"><span data-olk-copy-source="MailCompose">Attention: Kapitus is aware that individuals posing as recruiters&nbsp;</span>may be&nbsp;communicating with job seekers about supposed&nbsp;positions with Kapitus. Kapitus has received reports that the content and method of communication can vary, but messages may contain requests for payment (e.g., fees for equipment or training) and/or for sensitive financial information.</span></p> </div> <div> <p><span style="color: rgb(124, 146, 248);">Kapitus will <strong><u>never</u></strong> ask a candidate for employment for payment or financial information during the initial application or interview process. All open positions are posted in location specific employment portals available at <strong><u><a id="OWA1c01f2a9-bcc3-7fa1-1f42-a3e564bcfc76" class="x_OWAAutoLink" style="color: rgb(124, 146, 248);" href="https://www.perficient.com/careers" data-linkindex="1" data-auth="NotApplicable">w</a>ww.kapitus.com/careers</u>&nbsp;</strong><strong>&nbsp; </strong>All legitimate Kapitus job postings on employment sites will direct candidates to complete an application through these portals before completion of the hiring process.</span></p> </div> <div> <p><span style="color: rgb(124, 146, 248);">Candidates with additional questions or concerns regarding any recruiting communications or Kapitus’&nbsp;recruiting process in general should email <strong><u><a id="OWA4573487d-6c94-b52e-0613-1b1034189b61" class="x_OWAAutoLink" style="color: rgb(124, 146, 248);" href="mailto:recruiting@kapitus.com" data-linkindex="2">recruiting@kapitus.com</a></u></strong><strong><u>&nbsp;</u></strong></span></p> </div> <p></p></div><p>As a Data Science Intern, you will have the opportunity to work on real-world data science projects that directly impact business decisions. During your 10-12 weeks with us, you will focus on enhancing our credit risk prediction models, along with exploring new data sources and applying advanced machine learning techniques to improve the accuracy and interpretability of our underwriting models. Our department is responsible for developing and deploying machine learning models that support critical business functions across the organization, including Sales &amp; Marketing, Underwriting, Collections, and Finance. These models play a vital role in optimizing decision-making, improving efficiency, and driving business growth.</p> <p><strong>What You’ll Do: </strong></p> <p><strong>Credit Risk Prediction Model Enhancement</strong></p> <ul> <li>Develop a refined model with improved predictive power and actionable insights for underwriting decisions.</li> <li>Improve the accuracy and interpretability of our underwriting models by incorporating alternative data sources.</li> </ul> <ul> <li>Evaluate new feature sets from transactional and bank statement data.</li> <li>Test different machine learning techniques and optimize the model for better risk assessment.</li> </ul> <p><strong>Data Exploration &amp; Preprocessing</strong></p> <ul> <li>&nbsp;Work on data cleaning, feature engineering, and preparing the dataset for model development.</li> </ul> <p><strong>Model Development &amp; Evaluation</strong></p> <ul> <li>Build and refine machine learning models using appropriate techniques and evaluate their performance using metrics such as accuracy, precision, and recall.</li> </ul> <p><strong>Business Insights &amp; Recommendations</strong></p> <ul> <li>Translate model results into actionable business insights and propose ways to implement these findings.</li> </ul> <p><strong>Data Visualization &amp; Reporting</strong></p> <ul> <li>Create data visualizations to effectively communicate results and insights to business stakeholders.</li> </ul> <p><strong>What We Are Looking For:</strong></p> <ul> <li>Proficient in Python (Pandas, NumPy) or R for data analysis and manipulation.</li> <li>Experience with machine learning libraries such as scikit-learn, TensorFlow, or similar. Familiarity with algorithms such as regression, classification, clustering, etc.</li> <li>Ability to create clear and informative visualizations using tools like Matplotlib, Seaborn, or Tableau.</li> <li>Strong understanding of statistical methods for model evaluation and hypothesis testing.</li> <li>Ability to think critically and solve complex problems using data-driven approaches.</li> <li>Strong written and verbal communication skills, with the ability to present technical results to non-technical stakeholders.</li> </ul> <p>&nbsp;</p> <p><strong>Company Mission:</strong></p> <p>At Kapitus, we strive to empower every business to succeed by providing the best financing options – when they need it and how they need it. Whether we are working with a business directly or through a strategic partner, we will work diligently to provide the most convenient, cost- effective and appropriate financing solution for a business’s needs. We promise to keep the best interests of our clients at the center of the financing process by operating with transparency, fairness, and integrity. We will continue to empower small businesses to make educated financial decisions, as we have since our inception in 2006.</p> <p><strong>About Us:</strong> Kapitus is one of the most reliable and respected names in small business financing. As both a direct lender and a marketplace built with a trusted network of lending partners, we are able to provide small businesses the financing they need, when and how it is needed.<br>We’ve spent the past 15 years building a culture that makes us excited to come to work in the morning. Our company is fast paced, teammates need to be self-directed and have an internal motivation to do the right thing, even when the right thing takes a lot of hard work.<br>We show our teammates our appreciation by offering great benefits, competitive pay, and solid opportunity for growth.</p> <p><br><strong>Consideration will be given to qualified remote candidates residing in states where Kapitus and/or one of its subsidiaries has an established physical presence.</strong></p> <p>&nbsp;</p><div class="content-conclusion"><p>&nbsp;</p> <p>&nbsp;</p></div>