Data analyst intern
Technology domains: Tableau, Power BI, Python
Location: Paris, France
Duration: 6 months
Keywords: Internet of things (IoT), artificial intelligence (AI), data-driven real estate asset management, sensor data, smart buildings
Square Sense is a fast-growing platform that provides advanced data solutions to global real estate developers, investors and managers. The company builds AI-powered “building brains” that support the digital transformation of investment and asset management, and improve the operational and financial performance of real estate assets.
These brains provide real-time pattern interpretation of user community profiles and service performance, and enable autonomous optimization to greatly enhance the user experience for the tenants and the asset/portfolio management strategy execution such as investment, net income or ESG.
Square Sense was founded in 2017 in Paris by a multi-cultural team of talented engineers and data scientists.
Data analysis @ Square Sense
Square Sense is developing products to understand people's behavior and building performance using data collected from sensors and systems within a building. Our models infer knowledge using data from heating, ventilation, and air conditioning (HVAC) systems, lighting, smart meters, Wi-Fi, people counting & occupancy sensors, access control systems, elevators, air quality sensors. These models are based on statistics, probabilistic models, machine learning, and deep learning. The understanding of how a building is used and how it performs under various conditions is used to devise and implement strategies to reduce operating costs, improve the user experience, and increase revenue. Our goal is to develop decision-making support systems and autonomous optimization routines, both at the building level and at the portfolio level (i.e., for clients that own several buildings). An example of decision-making support is a product that quantifies the possible yearly energy savings effectively obtainable by improving the thermal insulation of the building given knowledge of how the building is used. An example of autonomous optimization is the automated and dynamic optimization of the thermal comfort and the energy consumption of the building given current and predicted building occupancy.
Data analysts at Square Sense are responsible for supporting decision-making using available data within client-specific projects (involving one or multiple buildings). Their tasks include quantifying relationships between different variables under various circumstances (e.g., actual or projected), and identifying trends and patterns. They work with the data produced by our data pipeline, which is developed and maintained by our engineers and scientists, and which collects sensor data, transforms this data using various algorithms and models, and stores the results into an analytical database. Data analysts use business intelligence software such as Tableau and PowerBI, as well as Python-based tools (Plotly, Dash, pandas, Matplotlib) to perform their tasks.
- To be enrolled in a master's or Ph.D. program in a quantitative discipline (e.g., statistics, operations research, bioinformatics, economics, computational biology, computer science, mathematics, physics, electrical engineering, industrial engineering) or equivalent educational program
- Experience with business intelligence (e.g., Tableau, Power BI) or data visualization tools
- A solid background in mathematics and statistics
- Attention to detail and strong focus on the accuracy of obtained results yet driven by achieving business impact through data analysis
- Willingness to work in a team, review work done by others, and take constructive feedback
- Written and spoken fluency in English
- Effective written and verbal communication skills
- Academic or industrial experience in a data analysis related field
- Applied experience with Python for data analysis tasks
- Experience using relational databases and non-relational databases
What we offer
- An experienced team with a very strong high-quality development mentality yet focused on fast and agile execution to achieve business impact
- A data-centric product, where gaining insight from data is at the core of the business
- A team of experienced and agile engineers and scientists responsible for making data available in an analytical database that is easily queryable using business intelligence tools
- A competitive salary
- Fast-growing early-stage startup: team size is expected to double in the next 12 months
- A multi-cultural team that is passionate about technology, regular team outings
- Open communication, flat hierarchy, and fast execution
- Flexible working hours, allowance for partial telecommuting
- A comfortable office in the center of Paris (Strasbourg – Saint-Denis metro station)
- Perform data analysis to help shape or meet specific business needs and goals.
- Collaborate with the project management, engineering, and research departments to understand business needs and devise possible approaches.
- Apply a rigorous, methodical, and logical approach when deriving insights from data.
- Assess the quality and impact of findings with respect to how well they meet business needs and goals.
- Report results and findings clearly and efficiently, both internally and externally.
- Discuss findings with other analysts and scientists and devise possible new directions and improvements.
- Propose possible new use cases to product management based on obtained findings.
- Develop production-ready dashboards.
- Collaborate with the product management department to define the scope of the proposed solution.
- Collaborate with the engineering department to devise possible production-ready solutions.
- Continuously improve the implemented solution by identifying issues, assessing its quality, and devising possible solutions.
- Work within a Scrum framework with other analysts and in collaboration with the engineering and research departments.
To apply for this position, please send us your CV to email@example.com with the subject line "Data analyst intern".