Lead Data Scientist, Timeseries ML & Optimization
Role details
Job location
Tech stack
Job description
TheAI Solutions team is in charge of developing AI use-cases for both external Schneider Electric customers (digital buildings, microgrids, industrial automation, etc.) and internal functions (HR, finance, marketing, customer support, etc.). We are looking for a Lead Data Scientist. Your responsibilities :
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interact continuously with internal or external customers to gain a good understanding of their needs, propose relevant solutions, and support them as needed,
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collect, evaluate and select Artificial Intelligence / Machine Learning use cases, with a focus on business value and business and technical risks - in partnership with the Product Managers
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specify, design, implement, test, validate, and industrialize machine learning, optimization, advanced data management, artificial intelligence, and analytic functions to be integrated in internal or external products, systems and solutions - i.e. from technical risk exploration to operational deployment,
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contribute to cutting-edge innovation / technology actions (e.g., prototype developments, experimentations, analytic competitions) involving research, standardization, development of intellectual property - patents, papers, open source -, partnerships, etc.
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apply maturation and development processes and good practices defined within the Artificial Intelligence Hub, and contribute to their updates in an ever-evolving context,
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share knowledge, teach and coach within the Artificial Intelligence Hub and beyond,
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promote Schneider Electric's strategy in the Analytics / Artificial Intelligence / Data Science domain through papers, blogs, conference presentations, and contribute to internal and external cross-function communities.
Requirements
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Master or PhD or equivalent diploma in optimization / operational research and timeseries machine learning / data science / artificial intelligence
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Additional education in signal processing, control theory, statistics is valuable.
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Additional education in genAI, agentic frameworks, etc. is valuable
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3-5 years of experience in optimization preferably with timeseries (optimal control / model predictive control / predict-then-optimize, optimal scheduling / planning), machine learning with timeseries (clustering, classification, profiling, forecasting, fault and anomaly detection, predictive maintenance), mathematical programming (efficient coding of vectors and matrix-based algorithms), visual analytics and data exploration.
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Mastered technologies are expected to include Model Predictive Control and Mixed-Integer Linear Programming. Experience with constraint programming, dynamic programming, stochastic programming, metaheuristics, reinforcement learning or other optimization technologies would be a plus.
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At least 2 years of experience in optimization modeling and application development preferably in the energy management field.
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An extra experience in genAI, probabilistic modeling or statistics is valuable
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Very good data analysis skills and data storytelling, ability to explain complex things in a simple way.
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Good knowledge of industrial python
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Good software engineering experience: capacity to code, debug, test and troubleshoot throughout the application development process and in agile mode
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Significant experience with data and machine learning libraries: numpy, pandas, scikit-learn, plotly, matplotlib, glpk, cplex, pyomo, polars, pyarrow, tensorflow...
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Working knowledge of git/github ; Knowledge of the pytest framework
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Possible knowledge or experience of devops tools, CI/CD with github actions, cloud (Azure, AWS, GCP)
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Very good communication skills, pragmatism, and rigor
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team player
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listening to others, and conveying messages in an accurate and effective manner
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able to explain complex concepts and features to anyone with different mindset/different skills - pedagogical skills.
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Leadership competencies
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Eager to understand business context and implications
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Entrepreneur mindset, contributing innovative ideas, taking risks, challenging status quo
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Sense of responsibility / ownership when facing difficulties. Resilience and trust in others.
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Network builder, promoting synergies within the company and with external partners
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Consistently involving all stakeholders in plans and decisions that affect them
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Fluent in english