Senior Machine Learning Engineer, Credit RiskMXN 400,000 - 600,000About AvivaWe are a Mexico City-based technology startup following a unique approach to unsecured credit for underserved communities. Aviva's physical onboarding kiosks build a bridge to those living in remote communities and provide a documentless 3-minute video onboarding for everyone in need of liquidity. This asset-light acquisition strategy, combined with a superior risk model based on computer vision and natural language processing, will allow Aviva to offer the lowest interest rates available to today's underserved.What you will doWe are looking for a ML engineer to pursue innovative approaches to credit decision: deciding whether to approve a new client, to offer a new loan to a past client, deciding the parameters of the loans, deciding which collection actions to take. We have several ongoing projects you may be interested in (such as using our lie detector to inform loan decisions). However, we will welcome fresh ideas to tackle our business problems. In the medium-term, we would like to lead new projects end-to-end (from conversations with stakeholders to properly define the problem, to deployment and monitoring of models).RequirementsMust-havesDegree in STEM field3+ years of professional experience using machine learning on tabular data.Familiarity with Git.Creative and strategic approach in solving hard people and technical problems.Nice-to-havesWe do not expect you to fulfill all the requirements below. But we are more likely to hire someone satisfying several of them.Verifiable track record of designing great ML models for tabular data (for instance, with good rankings in some Kaggle competitions).Experience in the financial industry.Experience with auto-regressive models (for instance, with Recurrent Neural Networks).Experience with Reinforcement Learning.Great python skills (deep knowledge of the language, writing clean code, designing the code architecture of large projects).Experience with end-to-end ML systems, cloud platforms, data pipelines and model monitoring.Attractive compensation package with stock options, fast-paced environment with many growth opportunities, relocation package, and possibility to work remote 3-4 days per week. We are also open to fully-remote candidates if they are a great match.#J-18808-Ljbffr
