About the Company
Soho is a real estate platform that helps users find their perfect "Property match" through a tinder-like matching feature and optimized search results. The platform leverages user preferences and interactions to improve property suggestions. Soho is a free-to-use platform that collects a significant amount of data on property popularity. With over 400,000 users browsing more than 100,000 properties monthly, Soho is experiencing rapid growth, backed by an experienced team with a history of successful tech startup exits.
About the Role
As the company's Data Scientist, this will be a fast-paced and collaborative role, working closely with the product, development, and business teams. You will be responsible for productising the data within the business to create improved application algorithms and prepare data for external consumption by third-party clients. Data tools used include Google BigQuery, Postgres DB, SQL, AWS AI suite (e.g., rekognition), Algolia AI, Mode.com, and several analytics/reporting tools.
Responsibilities
- Play a lead role in the rollout/management of any machine learning tools, modelling, and data engineering planning with the development team.
- Identify opportunities to leverage and productise the company’s data, and lead execution of data projects.
- Identify areas to improve data quality and be able to create pipelines or manipulate data.
- Build processes to extract, transform, and analyse data using various tools, especially SQL.
- Perform ad hoc analysis of data to support business decision-making.
- Data visualisation using a variety of tools, e.g., MS Excel or Mode.com, to communicate Soho’s data to both internal (team) and external (clients/partners) audiences.
- Take ownership of reporting/monitoring business metrics by setting up dashboards.
- Work with other teams (marketing, design, engineering) to drive overall business metrics.
Requirements
- Computer science or Engineering degree is required.
- Knowledge of SQL is a must, for data transformations and analysis.
- Experience with various data/storage formats (CSV, XML, Excel, relational databases).
- Previous experience with ML-based products and data engineering is essential.
- Experience in working with recommendation engines is a plus.
- Attention to detail and thoroughness in reviewing data quality.
- Ability to effectively communicate data and insights in various visual formats, like charts, graphs, histograms, etc.
- Ability to work productively and autonomously in a fast-paced environment.
- Knowledge or experience in quantitative modeling and statistical approaches to data (e.g., statistic regression, predictive modeling, recommendation engines etc.).
- Knowledge or experience with engineering will be an advantage.