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Soho is a real estate platform that helps users find their perfect "Property match" by allowing them to swipe properties they're interested in or not. The platform uses user preferences and interactions to improve property suggestions via a Tinder-like matching feature and optimize search results. Soho is a free platform that is unlocking a massive amount of data around property popularity, with over 400,000 users browsing through over 100,000 properties each month. The company is growing rapidly and is built by an experienced team who have founded and exited tech startups such as Airtasker (IPO) and Tank Stream Ventures.
About the Role
As the company's Data Scientist, this will be a fast-paced and collaborative role where you will work closely with the product, development, and business teams. You will be productising the data within our business both to create improved application algorithms as well as preparing the data for external consumption by third-party clients. The 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, modeling, and data engineering planning with our 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 analyze data using various tools, especially SQL.
Ad hoc analysis of data to support business decision-making.
Data visualization 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.
About You
You are an ideal candidate if you have the following skills:
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.
Be able to effectively communicate data and insights in various visual formats, like charts, graphs, histograms, etc.
Be able 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.
