Build pragmatic, scalable, and statistically rigorous solutions to various challenges from embedded solutions, autonomous cars, industrial applications, robotics and retail.
Locations (5)
Alcobendas, Madrid, Spain
Madrid, Madrid, Spain
Gdansk, Pomerania, Poland
Budapest, Budapest, Hungary
Frankfurt, Bavaria, Germany
Responsibilities
Build pragmatic, scalable, and statistically rigorous solutions to various challenges from embedded solutions, autonomous cars, industrial applications, robotics and retail.
Work with data and tasks related to computer vision, statistics, classical artificial intelligence, SLAM, robotics.
Work cross-functionally to define problem statements, collect data, build analytical models and make recommendations
Build and maintain data driven optimization models, experiments, forecasting algorithms and capacity constraint models
Leverage tools like Python, Tensorflow, Torch
Requirements
Degree in the field of quantitative analysis (e.g. Computer Science, Robotics, Mathematics, Statistics or other related field)
Build pragmatic, scalable, and statistically rigorous solutions to various challenges from embedded solutions, autonomous cars, industrial applications, robotics and retail.
Locations (5)
Alcobendas, Madrid, Spain
Gdansk, Pomerania, Poland
Madrid, Madrid, Spain
Budapest, Budapest, Hungary
Frankfurt, Bavaria, Germany
Responsibilities
Build pragmatic, scalable, and statistically rigorous solutions to various challenges from embedded solutions, autonomous cars, industrial applications, robotics and retail.
Design and develop engaging R Shiny applications, dashboards and visualisations to support clinical study monitoring, data review, safety analysis and evidence generation.
Use R and advanced statistical techniques to transform complex clinical and real-world datasets into meaningful and accessible insights.
Build scalable, modular and well-documented solutions, while continuously improving performance, usability and user experience.
Partner with cross-functional colleagues to ensure solutions follow relevant CDISC standards, regulatory requirements and internal quality standards.
Share your expertise in R and R Shiny, contribute to best practices and automation initiatives, and support the development of colleagues across the team.
Requirements
A degree in Statistics, Mathematics, Computer Science, Life Sciences or a related discipline, or equivalent relevant experience.
Data Scientist role focused on unlocking insights from datasets using IoT, machine learning, and AI to solve global challenges in fraud detection, cancer research, and national intelligence.
Compensation
The projected compensation range for this position is $77,600.00 to $176,000.00 (annualized USD).
Responsibilities
Unlock secrets held by datasets using IoT, machine learning, and AI
Work closely with clients to understand questions and needs
Dig into data-rich environments to find information puzzles
Develop algorithms and systems to turn disparate data points into objective answers
Provide deep understanding of data and its potential use
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