Data Science Intern (Paris, Berlin, Hamburg, Vienna)
PriceHubble, France
Job Description
PriceHubble is a PropTech company with over 80 employees, set to radically improve the understanding and transparency of real estate markets based on data-driven insights. We aggregate and analyse a wide variety of data, run big data analytics and use state-of-the-art machine learning to generate high-quality valuations and predictive analytics for the real estate market. We are headquartered in Zürich, with offices in Berlin, Paris, and Tokyo. We work on international markets and we are backed by world-class investors. We have a startup environment, low bureaucracy, and an international team and business.
Your role
Data is at the core of PriceHubble. We process a wide variety of data from multiple sources. As a data science intern, you will be exposed to important parts of the data value chain within an AI company, such as data engineering and machine learning.
Joining the Value team, you will work closely with a team of data scientists and software engineers on real estate valuation models. Your daily challenges will be to explore new sources of data, clean datasets and extract amp; create new features. You will perform quantitative analyses on real estate portfolios. You will contribute to present results and provide valuable insights to our customers.
Responsibilities
- Perform quantitative analyses on real estate portfolio data.
- Support the analytics lifecycle: Data Cleaning, Data Exploration, Feature engineering, Predictive modelling.
- Preparation, aggregation and manipulation of data from a variety of internal and external sources. Handle potentially incomplete datasets.
- Identify modeling issues, and continuously provide ideas to improve our models.
- Contribution to high-quality client-facing presentations.
Requirements
- BSc or MSc in Computer Science or equivalent (Statistics, Mathematics, Economics, Finance).
- Proficiency in Python, and familiarity with a Jupyter Notebook / Pandas environment.
- In-depth understanding of basic data structures and algorithms.
- Understanding of core machine learning concepts.
- Familiarity with software engineering best practices (clean code, code review, test-driven development, .) and version control systems.
- Interest and understanding of the real estate market and urban related data is a strong advantage.
- Experience with ETL and data processing tools we are using is an advantage: Luigi/airflow, PySpark, PostgreSQL, PostGIS and kubernetes.
- Comfortable working in English; you have a great read, good spoken command of it.
Benefits
On top of joining a team of ambitious, qualified people you may also enjoy our benefits:
Flexible work hours
Competitive salary
Casual dress code
Lamp;D program
Well-located offices
Free snacks, fruits, coffee, beers, sodas