Title: Data Scientist- Machine Learning
Bangalore, IN
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ENERGY THAT CHANGES: Innovative and sustainable key technologies are prerequisites for renewable energy supply. More than 3,000 employees from 18 countries work to ensure that SMA is actively helping to promote the production and development of PV system technology worldwide. Would you like to play a part in shaping the energy supply of the future? Welcome to SMA. be energy. Your energy can thrive with us. Respond to changes in an active, bold and targeted way. be flexible. Conditions can change, so our work schedule models offer you a solution. be family. A sense of community and camaraderie is important to us. We offer work-life-balance. |
Description
Are you passionate about data, models, and real-world impact? Join our Data Science & Monitoring team and help shape the future of intelligent energy systems!
We design and implement data-driven solutions that make energy systems smarter, more efficient, and sustainable. You’ll work on exciting projects involving machine learning, anomaly detection, time series analysis, and predictive modeling, all within a cloud-native, collaborative, and interdisciplinary environment.
If you thrive on solving complex problems, enjoy teamwork, and want to make a tangible impact through data science—this role is for you.
Key Responsibilities
• Develop Advanced Machine Learning Models
Design, build, and deploy machine learning models for anomaly detection, prediction, and performance optimization across complex energy systems.
• Analyze and Interpret Large Datasets
Explore vast amounts of operational and sensor data to uncover trends, detect anomalies, and generate actionable insights.
• Data Preparation and Visualization
Clean, preprocess, and visualize time-series and event data to support effective model development and result interpretation.
• Integrate Models into Production Systems
Collaborate with software engineers and cloud experts to deploy and monitor data science solutions in scalable, production-grade environments.
• Drive Innovation and Model Explainability
Continuously enhance model transparency, interpretability, and performance through advanced algorithms, monitoring, and experimentation.
Requirements
• Experience of 8 years plus.
• Proficiency in Python and key data science libraries (e.g., pandas, scikit-learn, TensorFlow, PyTorch).
• Strong foundation in machine learning algorithms, statistics, and anomaly detection methods.
• Experience with cloud platforms (e.g., Azure, AWS, or GCP) and scalable data processing workflows.
• Skilled in data wrangling, feature engineering, and visualization tools such as Matplotlib or Plotly.
• Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or a related field (PhD a plus).
Desired Characteristics
• Familiarity with forecasting, time series modeling, and predictive maintenance use cases.
• Background in energy systems, operations research, or industrial analytics.
• Experience deploying data science models to production using CI/CD pipelines or MLOps tools.
• Strong analytical, communication, and problem-solving skills with a proactive mindset.
• Excellent proficiency in English; other languages are a plus.
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#bethechange We look forward to receiving your application. ∗ SMA is committed to diversity and equal opportunity - unattached of gender, age, origin, religion, disability or sexual orientation. |
