Senior Data Scientist

KONE is a global leader in the elevator and escalator industry, making people's journeys safe, convenient, and reliable with smart and sustainable People Flow®. In a world where cities are constantly evolving and more and more people choose to live in them, we at KONE stand with one clear aim: to shape the future of cities. We make urban life more vibrant and livable. And we do it by enabling safe, sustainable, and effortless people flow for all. We help cities leave a positive mark on the planet - for the next century and beyond. We shape the future of cities.
KONE Technology and Innovation Unit (KTI) is where the magic happens at KONE. It's where we combine the physical world - escalators and elevators - with smart and connected digital systems. We are changing and improving the way billions of people move within buildings every day. We are on a mission to expand and develop new digital solutions that are based on emerging technologies.
KONE R&D brings together top talent from different disciplines into an industry-leading product and technology organization. We thrive in solving complex customer challenges, connecting legacy with the latest technologies across hardware and software engineering. In fact, roughly half of our R&D roles are in software. Agile ways of working mean that we are better able to meet our customers rapidly evolving needs for speed and innovation, in a global environment.
R&D unit in KTI is responsible for developing digital services at KONE. It's the development engine for our Digital Services such as KONE 24/7 Connected Services, Office Flow and Partnership Ecosystem. Our common goal at KONE is to keep the end users safe and people flow uninterrupted. KONE moves 2 billion people every day and that means our services can really make cities better places to live

Job Description:

• Design, develop, and deploy predictive and recommendation models to support product intelligence and data-driven decision-making.
• Build and maintain end-to-end analytics pipelines on AWS and Databricks, including data ingestion, transformation, feature engineering, model training, and evaluation.
• Perform advanced data analysis on large-scale datasets to uncover patterns, trends, and actionable insights.
• Collaborate with data engineering teams to leverage Databricks, Spark, and cloud-native AWS services for scalable analytics and model deployment.
• Translate business and product requirements into predictive analytics and recommendation solutions with measurable impact.
• Ensure solutions adhere to transparency, explainability, data governance, and security standards.
• Deploy solutions into production and support monitoring, refinement, and performance tuning using best practices.
• Work closely with product managers and engineering teams to continuously improve model effectiveness and business value.
• Mentor junior team members and promote best practices in analytics and ML.

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