Über
is revolutionizing industrial AI with a powerful platform that enables businesses to harness the full potential of their operational data. With advanced capabilities like digital twins, natural language processing, normal behavior modeling, and machine vision, we create real-time virtual replicas of physical assets, enabling predictive maintenance, performance simulation, and operational optimization. Our AI-driven models empower companies with scalable solutions for anomaly detection, performance forecasting, and asset lifetime extension—all tailored to the complexities of industrial environments.
Cutting-Edge AI Innovation
– Join a team at the forefront of AI, developing groundbreaking solutions that shape the future. Meaningful Impact
– Work on AI-driven projects that drive real change across industries and improve lives. Join us in developing and applying
cutting-edge machine learning solutions for commercial and industrial applications. As a Data Scientist, you will partner with project teams to develop and deliver customer solutions, working on challenging problems in
forecasting, demand planning, renewable energy optimization, anomaly detection, and prescriptive maintenance
. Key Focus Area: We are looking for candidates with strong
expertise in
forecasting and time series analysis to support our growing demand planning, power/price forecasting, and predictive analytics capabilities. You will lead all phases of the data science process from data exploration and processing, feature selection and engineering, model
training and testing, to information synthesis and deployment. You will work closely with team members who have deep technical skills and a passion for clean energy and industrial optimization.
Build forecasting models for demand planning, power/price prediction, and supply chain optimization
~ Develop time series models using traditional methods (ARIMA, Prophet) and modern ML approaches (LSTM, Transformers)
~ Partner with project teams in developing and applying ML
expertise to deliver customer solutions
~ Independently and effectively engage with external technical stakeholders and subject matter experts to understand and solve critical business problems through artificial intelligence
~ Design and deploy machine learning models for commercial and industrial applications, including anomaly detection, prescriptive maintenance, and optimization
~ Lead all phases of the data science process from data exploration, feature engineering, model training, testing, and deployment
~ Apply data mining techniques, statistical analysis, and build prediction systems
~ Create automated anomaly detection systems and track performance
~ A strong understanding of Data Science, including basic elements of machine learning, statistics, probability, and modeling
~ Strong experience with time series analysis and forecasting techniques (ARIMA, exponential smoothing, Prophet, LSTM, etc.)
~ Quantitative background with experience working with time series data and strong coding skills
~ Background in deep learning and neural network architectures for sequence modeling
~ Experience with Data Science programming languages: Python (required), R,
Matlab
~ Familiarity with Deep Learning frameworks such as TensorFlow and
PyTorch
, with experience in at least one
~ Applied knowledge of ML techniques/algorithms including linear models, neural networks, decision trees, Bayesian techniques, clustering, and anomaly detection
~2+ years of experience in building machine learning models
~ Experience with cloud platforms (AWS, GCP, or Azure)
~ Ability to form strong working relationships with team members, customers’ technical teams, and executive leadership
~ Degree in Computer Science, Statistics, Physics, Mathematics, Engineering, or a related field
Graduate or Doctorate degree (or 5-8 years of equivalent experience) in one of the fields above
~ Experience and knowledge of renewable energy technologies, especially applying data analytics techniques in the domain
~ Experience with LLMs, RAG systems, and generative AI applications
~ Exposure to scalable ML model deployment and
MLOps practices
~ Coding Challenge: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws.
Sprachkenntnisse
- English
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