Grupo QuintoAndar | Staff Data Scientist (Women Applicants Only)

About this role

<p></p> <p><strong>About Grupo QuintoAndar</strong></p> <p>We are Grupo QuintoAndar, the largest real estate ecosystem in Latin America. Guided by a shared purpose of helping people love where they live, we have a diversified portfolio of brands and solutions across different countries in Latin America, covering all phases of the housing journey. We also have a Technology Hub in Portugal. We develop technology and innovation to transform and enhance the overall living experience.</p> <p>With the support of a world-class team of investors and advisors, including Kaszek, Qualcomm, General Atlantic, and SoftBank, Grupo QuintoAndar is currently valued at over USD 5.1 billion and continues to grow year over year.</p> <p>Here, you will work with top professionals in the market, in an environment that breathes innovation, collaboration, and high performance. To learn more about our story, visit:<a href="https://grupoquintoandar.com/pt/"> </a><a href="https://grupoquintoandar.com/pt/">https://grupoquintoandar.com/pt/</a>.</p> <p>&nbsp;</p> <p><strong data-path-to-node="1" data-index-in-node="0">Why is this a diversity-focused position for women?</strong><br><br>At QuintoAndar Group, we are committed to promoting gender diversity across our teams. We want to see more women in strategic positions within our technical teams, and we believe we can achieve this through intentional opportunities and actions. This is part of a larger plan to strengthen an equitable culture across multiple aspects. It is worth noting that for this vacancy, our selection process has not undergone any changes in terms of stages or evaluation methods.</p> <p>&nbsp;</p> <p><strong>Location &amp; Remote Work</strong></p> <p>Our technology team operates under a "remote-first" model, which means we work from home and can live anywhere in Brazil. We also offer the option of working from our São Paulo offices or partner coworking spaces, up to twice a week.</p> <p>&nbsp;</p> <p><strong>Hiring Process Stages</strong></p> <p>The stages of our hiring processes aim to assess your experiences and allow you to meet our teams and explore career opportunities. They are structured as follows:</p> <ul> <li>Application</li> <li>Interview with Recruiter</li> <li>Tech Screening</li> <li>Technical Interviews with Data Team</li> <li>Offer</li> </ul> <p>&nbsp;</p> <p><strong>About the Area</strong></p> <p>In our Data Science team, you'll have the chance to work as a part of our product squads delivering features that enrich our product and a first class experience that we are known for. You'll work alongside brilliant minds, with different skills: Product Managers, Designers, UX Writers, Data Scientists, Machine Learning Engineers, Software Engineers, etc. Be prepared for the job of your life - hard challenges, high expectations, intelligent life at work, meaningful conversations, outstanding productivity.&nbsp;Some of the specific problems we work in the Data Science team include search and recommendation systems; customer experience enhancement using ML such as in automatic routing of tickets; pricing, liquidity and credit models; building a platform that enables us to develop and deploy all those solutions.</p> <p>&nbsp;</p> <p><strong>Responsibilities</strong></p> <ul> <li>Architect, develop and deploy machine learning systems to production. The main use cases are related to chatbots and search.</li> <li>Design and execute experiments.</li> <li>Analyze a wide variety of data (structured and unstructured, observational and experimental) to improve current models or create new ones</li> <li>Apply the scientific method to develop LLM-powered applications, including testing different prompts, exploring and understanding LLM capabilities, evaluating agents and prompts, assessing AI application guardrails, and building PoCs to validate the feasibility of generative AI for product features.</li> <li>Participate actively in discussions and decisions regarding the whole Data Science chapter (Guilds, Design Reviews, Demos, etc.)</li> </ul> <p>&nbsp;</p> <p><strong>What we are looking for:</strong></p> <ul> <li>People that are seeking to learn and deliver real impact through Data Science</li> <li>Expert knowledge of machine learning concepts: regression and classification, clustering, neural networks, feature selection, cross-validation, curse of dimensionality, bias-variance tradeoff, model explainability, etc.;</li> <li>Good understanding of the engineering challenges to deploy machine learning systems to production;</li> <li>Proficiency in Python;</li> <li>Some knowledge or experience with Deep Learning</li> <li>Experience with technical advice for other data scientists (technical leadership);</li> <li>Excellent written and verbal technical communication skills. We're looking for someone who loves Data Science &amp; Machine Learning and is willing to share his/her knowledge with the other members of the Data Science Chapter;</li> <li>Good English skills (verbal and written) is mandatory.</li> </ul> <p>&nbsp;</p> <p><strong>You'll stand out if you:</strong></p> <ul> <li>Have a MSc. (or Undergrad + intense experience) in machine learning, data science, information retrieval, ranking systems, recommender systems, natural language processing or other relevant fields.</li> <li>Have experience with applied generative AI: AI agents, prompt engineering, LLMs finetuning (lora, qlora, peft), LLM routing, LLM monitoring, LLM guardrails</li> <li>Have experience working at fast-growing startups.</li> </ul> <p>&nbsp;</p> <p><strong>Important</strong></p> <ul> <li>Our hiring process starts with the application! If you truly want to be part of our team, please complete this step of the process. We analyze all candidates individually and provide feedback to all applicants.</li> <li>All communication will be conducted via email, so please stay tuned for our messages and release the domain @quintoandar.com.br to ensure our emails are not sent to spam.</li> </ul> <p>&