SR Data Scientist


Full Time Senior-level / Expert USD 68K - 135K *
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La Haus

¿buscas una inmobiliaria? tenemos una buena noticia, somos mucho más. la tecnología y oferta de finca raíz harán más fácil la compra de tu vivienda nueva.
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La Haus has the goal of making financial and geographic freedom accessible to millions of households in Latin America. We are transforming the real estate industry with world-class technology, data, and customer service. Technology provides efficiency and fluidity in our processes, data achieves transparency and precision, and personalized customer service brings the human touch to the most important financial decision for most people: Buying a home or starting an investment project.
As a Data Scientist, you provide our home buyers an experience that they would perceive as intelligent. In other words, customers should get a sense that the data we collect about them and their search preferences are handled in an intelligent way to improve their home-buying experience.

We are looking for a Hauser that...

  • Is guided by Human Sense, always with respect and empathy for others
  • Is an example of Transparency
  • Has an Innovation mindset, always looking for the best way to do things
  • Works with Autonomy, is the owner of their future
  • Is Humble, can see the opportunity to learn from any person and situation
  • Always goes the extra mile, working with commitment and dedication
  • Keeps it Simple. Remember... less is more

Main responsibilities of the role:

  • Improve existing machine learning models for predicting  commercial success of residential developments in México and Colombia.                                                                                       
  • Improve existing models for estimating the fair price of a new residential unit based on location, characteristics, demand etc.                                                                                           
  • Develop statistical procedures to score the credit-worthiness of residential developers.                                                                                      
  • Work together with other technology teams to ensure the production of high-quality historical data for training.                                                                                                   
  • Develop new statistical models for anticipating credit risk for home buyers.                                                                                                               
  • Monitor and supervise the correct functioning of all developed algorithms.                                                                                                           
  • Contribute to the continuous improvement of the team’s technical knowledge.                                                                                                         
  • Be in constant and close communication with Fintech product managers and tech leads,  to gain a deep understanding  of product and business needs and how they could be satisfied with data science and ML tools.                                                                                     
  • Be proactive, suggest simple, effective solutions that are easy to implement and maintain.                                                                                 
  • Be propositive: suggest improvements in the data capturing, representation and storing procedures.                                                        
  • Know and use methodologies for the development of predictive models CRISP-DM and SEMMA, paying special attention to aspects related to business understanding and integration.                                                                                             
  • Stay updated on the latest developments and trends in the fields of ML, DL, Deep RL, as well as the technologies and architectures used for their deployment.                                                                                                       
  • Be empathetic towards PMs and the commercial side of the company, but firm in pushing forward a technical, data driven approach.                                                                                                           
  • Be didactic in the divulgation of what ML and predictive analytics can and cannot do.                                                                                                           
  • Ask smart questions, assume risks and defend new ideas.                                                                                                                                                                                                             

Key requirements:

  • +5 years experience with data analysis and data manipulation
  • Experience developing predictive models (statistical or with ML)
  • Python (scikit-learn, NumPy) or R and SQL (advanced queries)

Benefits of working at La Haus:

  • A dynamic work environment, with an entrepreneurial spirit in which we love to work as a team
  • Competitive compensation package
  • Health insurance
  • 15 vacation days + 5 personal days
  • Working fully remote with an international team
​​Learn more about La HausVídeo: conoce un poco más de nosotrosAsí planea crecer La Haus en México con nueva inversión de $100 MM USDLa Haus entra a la élite del emprendimiento al ser admitida en la red Endeavor#BeHauser

* Salary range is an estimate based on our salary survey at

Tags: Credit risk Data analysis FinTech Machine Learning ML NumPy Python R Scikit-Learn SQL

Perks/benefits: Career development Competitive pay Health care

Region: Remote/Anywhere
Job stats:  13  3  0
Category: Data Science Jobs
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