Senior Data Scientist (f/m/d)

A job that inspires you

• Lead the technical implementation of sensor and IoT projects, from concept to production-ready deployment in the energy industry, ensuring robust and high-quality solutions

• Evaluate and implement cutting-edge ML/AI models in academic papers for energy applications, and communicate findings to shape project strategies

• Oversee the development, implementation, and deployment of state-of-the-art ML/AI models and technologies in digital pipelines together with IoT, Data, and ML Engineers

• Guide and mentor junior data scientists and collaboration partners, adding to and embracing FutureLab’s environment of continuous learning and improvement

• Drive the venturing of innovative R&D projects, from elaboration of technical ideas and concepts, through development of integrated hardware- and software prototypes and business development

• Work collaboratively within cross-functional teams and across partner organisations

• Communicate effectively technical requirements and business interdependencies to ensure alignment of project and engineering goals

• Stay ahead of emerging technologies, state-of-the-art components, and best practices in the areas of robotics, industrial IoT, and AI in the energy industry

A background that convinces us

• University degree (Master or PhD) in Computer Science, Statistics, Engineering or related fields

• Over 6 years of professional experience in applied data science or Machine Learning, ideally in an industrial or energy setting

• Profound knowledge in digital signal processing and insights into retrieving vital information from transmitted and received electromagnetic signals

• Strong software development skills with expertise in Python and MATLAB, along with hands-on experience using data science tools and libraries (e.g. NumPy, SciPy, Matplotlib, Scikit-learn, PyTorch (or equivalent), and Jupyter Notebooks)

• Knowledge of the mathematical foundations of statistical inference and forecasting such as time series analysis, multivariate analysis, cluster analysis, and optimization

• Extensive hands-on experience in developing, deploying and monitoring Machine Learning models

• Experience in working in the cloud, ideally Azure, with an emphasis on data and Machine Learning tools

• In-depth knowledge about the energy industry, its mechanisms, and challenges (professional experience in the energy industry is a plus)

• An experimental and entrepreneurial mindset and a desire to build things from scratch or optimize ones that already exist

• Outstanding communication skills with the ability to communicate complex technical ideas, regardless of the technical capacity of the audience

• Passion for technology and the inner desire to solve problems and move things forward

• Fluent in spoken and written English; German is a plus

Skills to Set You Apart

• IoT expertise: experience working with IoT or sensor data

• Solid understanding of chemometric techniques such as multivariate analysis (e.g. PCA, PLS), spectral preprocessing, and calibration model development

• Experience in time-series analysis, anomaly detection, or predictive maintenance using remote sensing data

• Experience in chemical engineering or understanding the chemical composition of different liquid insulators is a plus

An environment that motivates you

• A role full of challenges, where we will collaboratively design a successful onboarding process

• A respectful work atmosphere where mutual trust and respect play a crucial role in teamwork

• A modern work environment that ensures a balanced work-life balance through flexible working hours and the option for home office

• A diverse range of personal and professional training and development opportunities

• A strong network, as we prioritize collegial exchange across business units, offering various perspectives

• A secure provision with attractive compensation and additional benefits, such as in-house sports offerings

• 40 hours work week and 30 vacation days

• 100% paid travel time, including business trips (>50km), in first-class train travel

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