At Naya Homes, we’re building a property management and hospitality platform that empowers homeowners and real estate developers to increase their financial returns through short-term and vacation rentals while removing their operating burden. As we scale, we will be uniquely positioned to leverage our data to unlock a new asset class in Latam.
**Our team is looking for a talented and innovative Data Scientist focused on revenue model prediction. The purpose of this role is to build, test, and iterate predictive revenue models in order to increase accuracy and self-confidence in achieving projected results. A daily forecasting system will also be developed, automating price distribution per unit based on historical data, market trends, seasonality, and other relevant factors. In order to develop an industry-leading predictive revenue model, we encourage creativity and experimentation.
Forecast future revenue accurately by developing, testing, and iterating predictive revenue models.
Prepare and analyze large datasets containing historical revenue data, market trends, seasonality patterns, and other relevant variables.
Identify patterns, correlations, and trends within the data using statistical analysis and machine learning algorithms.
Identify business objectives, define revenue forecasting goals, and align revenue forecasting with broader organizational goals in collaboration with cross-functional teams.
Enhance the accuracy and reliability of predictive revenue models by developing and implementing innovative approaches and methodologies.
Utilize external data sources, industry benchmarks, and emerging market trends to enhance revenue prediction.
Automate the daily forecasting process to enable automatic price setting per unit, taking historical data, market conditions, and seasonality into account.
Monitor and evaluate model performance on an ongoing basis, making necessary adjustments to improve accuracy and effectiveness.
Communicate model outputs, insights, and recommendations to stakeholders at all levels using clear and concise reports and visualizations.
Collaborate with the team to transform the predictive revenue models into a unique recipe that sets us apart in the industry.
**An undergraduate or graduate degree in Data Science, Statistics, Computer Science, Mathematics, or a related field is required.
Expertise in revenue forecasting, pricing, or revenue optimization with 3+ years of experience as a Data Scientist.
Statistical analysis, forecasting, and machine learning expertise.
Proficiency in programming languages such as Python or R, and experience with data manipulation libraries (e.g., Pandas, NumPy) and machine learning frameworks.
Data preprocessing, feature engineering, and experience with large datasets.
Solid understanding of statistical modeling techniques and experience applying them in a business context.
Familiarity with time series analysis, regression analysis, and other forecasting techniques
Excellent problem-solving skills and ability to think creatively to develop innovative solutions.
At Naya Homes we celebrate diversity and are committed to providing an environment of mutual respect where equal opportunities are available to all.