R&d Lead Data Scientist

6 mesi fa

Milano, Italia Schindler A tempo pieno

**Location: Milan, Milano e Lombardia, Italy**
**Job ID**: 74957

**We Elevate... You**:
Join Schindler and help us elevate our world: Use your skills to allow megacities to grow. With our elevators and escalators, we keep the urban world moving.

Since 1874 Schindler has been a Citymaker with proud reputation for elevating not only buildings, but the well-being of everyone who lives and works in them. People, passion, and innovation are the pillars of our success.

More than one billion people put their trust in Schindler each and every day. Our many years of experience and innovative drive make us the number one supplier in the Swiss elevator and escalator business. Join the Schindler team and help us improve the world of mobility: Use your abilities and help us move people.

**Join us as a**

**R&D Lead Data Scientist (M/F/d)**:
**We Elevate... Your Responsibilities**:
In this role, you will be part of our Milan Software Development Hub, an agile team that develops modern software tools to help shape the next-generation elevator’s software to meet high quality and safety standards for Schindler’s products.

We are looking for a passionate out-of-the-box thinking person who wants to create insights for our connected elevators in the cloud. You will lead a team of engineers to design, test, and maintain our analytic solutions for elevators bringing in expertise in data acquisition, data processing, data analytics, machine learning, and predictive maintenance.

Your new challenges will include:

- Leveraging the data coming from roughly 0.5 million elevators and escalators connected to the cloud, defining diagnostic and establishing solutions for data ingestion from sensors and control systems while turning the collected data into actionable insights
- Working on all stages of data science related projects starting from understanding data to implementing the analytic output into digital solutions for business stakeholders or R&D product improvements
- Supporting the development of data architecture and data models

**We Elevate... Your Best Self**:
You are a self-directed and self-organized, highly responsible, and reliable team player. Your abilities to inspire, mentor and guide both on-site and remote teams pair with your open mind and for new technologies and agile development. You foster an effective communication in an international organization and can lead by example.
- Master’s degree in computer science, software engineering, physics, mathematics and/or equivalent technical fields
- Previous experience with technical leadership or project management
- Strong knowledge in statistics and Machine Learning, experience in Deep Learning and NLP is a plus
- Solid experience in Python and with data science and machine learning libraries such as Scikit-learn, Numpy, Scipy, Pandas, Pytorch, Spark or equivalent
- Proficient knowledge of Azure and Microsoft tools (DataBricks, AzureML) is preferred, background in similar solutions such as AWS are positively considered as well
- Working proficiency in English, Italian and German are a plus

**We Elevate... You**:
You will get immediate access to a variety of benefits by working for a TOP employer:

- Flexible work schedule and comfortable workspace in PoliHub Innovation District, Milan
- Development opportunities: You start with a position-specific familiarization and are supported by us through professional and personal training measures
- Work-life balance: We enable you to conciliate your professional and private life through flexible working hours
- Corporate benefits: Benefit from our various employee discounts
- Diversity: We promote a culture of diversity
- Working in a dynamic environment with an interdisciplinary team of specialists

**Can You Elevate Us?**:
At Schindler Group we value inclusion and diversity, and practice equity to create equal opportunities for all. We endeavor that all qualified applicants will receive consideration for employment without regard to age, race, ethnic background, color, religious affiliation, union affiliation, gender, gender identity, sexual orientation, marital status, national origin, nationality, genetics and health or disability.

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