Senior (Applied) Data Scientist Lisboa

Senior (Applied) Data Scientist
Lisboa
Lisboa, Lisboa, Portugal

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Price
Hubble is on a mission to transform how real estate and financial professionals make decisions. We’re a
- growing European B2B Saa
S company that leverages the power of AI and big data to bring
- level transparency and insight to the property market. Our digital solutions empower clients across the real estate value chain – from banks to asset managers – with the most precise property valuations and
- looking market intelligence. Already live in 11 markets across Europe, Asia, and North America, and backed by a team of 200+
- thinkers, Price
Hubble is scaling fast and going global.

The opportunity

At Price
Hubble, we organize our teams into Tribes. Each Tribe is responsible for a specific part of our product. They identify customer needs, create solutions, and ensure everything runs smoothly. Each Tribe operates independently, managing all aspects of its area. Engineers rotate between project teams and a group focused on maintenance and technical improvements.

The Property Intelligence Tribe provides insights to make informed real estate decisions. This includes assessing property values, tracking market trends, evaluating investment opportunities, and improving property management. Our mission is to deliver accurate property information for every residential property in our areas of operation. In that, Tribe members create the unique insights and intellectual property that drive our products.

The Tribe is a distributed team of engineers from 6 nationalities, located in 5 different European countries.

As an applied Senior Data Scientist, you will work on the ML systems that drive the core services of our platform. You will design, implement, and maintain Automated Valuation Models (AVMs) that professionals trust for assessing residential property values.

The impact you will have

• Develop product features that directly drive revenue growth. Our valuation models are major selling points for our customers.
• Navigate
  - value
  - offs to make decisions that deliver value to customers at an appropriate cost.
• Implement solutions that work well in over 10 countries, while considering local specifics in your model.
• Lead a project from concept to launch, working with a temporary team of engineers.
• Raise the bar and drive the team to deliver
  - quality products, services, and processes.
• Improve the performance and
  - efficiency of our ML models and pipelines at scale.
• Maintain and monitor the ML systems owned by your team.

Requirements

• A
  - oriented mindset and enthusiasm for contributing to
  - facing products. For you, ML is a means to an end – you're focused on delivering value to customers.
• Excellent English communication skills, both spoken and written, that allow you to communicate effectively with
  - functional partners and mentor fellow engineers. In our distributed team setup, strong writing communication skills are essential.
• Hands-on, you value writing clear, simple, and maintainable code. You understand that code is read more often than it is written.
• You embrace a growth mindset. You always continue learning and always seek new challenges.
• Over 3 years of industry experience applying machine learning to solve business problems and writing production ML pipelines.
• AI fluency. You use AI tools daily in your development workflow. You understand what works and what doesn't, and you know how to get better results faster.

Bonus

• Previous experience in Prop
  Tech.
• Proficient in working with geospatial data and leveraging geospatial features.

We're actively seeking applications from candidates of all backgrounds.

Join an ambitious and hungry team and enjoy the following benefits:

? Competitive salary because we always want to attract the best talents.

? Learning & Development program - We want you to feel happy, confident about improving your skills, experience level as well as your personal development success.

? Very
- located offices with a great remote work policy and the possibility to work from different places.

? Flexible working hours and work life balance.