Senior AI Industry Researcher at Schneider Electric USA, Inc

Posted in General Business 13 days ago.

Type: Full-Time
Location: Andover, Massachusetts





Job Description:

The AI Industry Researcher will be working with the Strategy and Innovation AI Research team to identify, evaluate and develop advanced Analytical, Machine Learning and AI Solutions for Schneider Electric's AI HUB and its internal and external customers. The core challenges will be to identify and develop strategic, innovative and disruptive solutions for Schneider Electric and its customer by leveraging the Schneider DNA and cutting-edge AI/ML technologies.

Key Responsibilities:


  • Take ownership for an entire project workstream or work with your colleagues jointly on a bigger project.

  • Provide AI Research Services to Schneider Electric Business, Clients and Partners

  • Develop Next Generation AI and Data Products together with Schneider Electric Clients and Partners

  • Research and survey industrial reports and technical papers on latest industrial trends, case studies, models and methodologies in the areas of team's research.

  • Successfully develop, conceptualize and test various statistical, AI and machine learning solutions to solve the future challenges.

  • Integrate the outcomes into the existing Schneider EcoStruxure Landscape to elevate Schneider Electric's ability to create value for clients in areas and through means not immediately apparent to clients

  • Researches, develops and maintains machine learning and statistical models for business requirements.

  • Partners with lines of business to translate business analytic problems into technical solutions and actionable recommendations across the organization

  • Work across the spectrum of statistical modelling including supervised, unsupervised, & deep learning techniques to apply the right level of solution to the right problem

  • Build frameworks leveraging APIs to industrialize AI models across the organization

  • Coordinate with different functional teams to monitor outcomes and refine/ improve the machine learning models

  • Build frameworks leveraging APIs to industrialize AI models across the organization

  • Collaborate with data and software engineers to enable deployment of models that will scale across the company's ecosystem

  • Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown)


AI Industry Researchers in Data and AI projects following state-of-the-art approaches for project execution from adapting existing assets to Analytics use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases, and engaging in fundamental research to develop novel solutions.

Basic Qualifications:


  • Master's or Ph.D. in Computer Science, Statistics, Engineering, Physics, Mathematics, Economics.

  • One or more year of Data Science experience for Ph.D. candidates and more than 3 years for master's candidates

  • Minimum 3 years of experience in at least one of the following - Supervised and Unsupervised Learning, Classification Models, Cluster Analysis, Neural Networks, Non-parametric Methods, Multivariate Statistics, Reliability Models, Markov Models, Stochastic models, Bayesian Models, Genetic Algorithms, Fuzzy Logic, Inference Systems

  • Experience with deep learning architecture and models such as CNN/RNN/LSTM/Transformer, time series, graph neural networks.

  • Minimum of 3 years of experience in various statistical and machine learning models, data mining, unstructured data analytics in corporate or academic research environments

  • Minimum 3 years of experience in data science workflows and methodologies, and tools such as Python, MATLAB, C++, Java, SQL, Visual Studio Code, Jupyter Notebooks, TensorFlow, PyTorch.

  • Basic knowledge of Microsoft Azure, AWS, or other cloud platforms.

  • Strong verbal and written communication skills in English


Preferred Qualifications:

  • 3 or more years of work and/or research experience in relevant domains (Energy, Industrial Automation, Oil & Gas, Chemicals, Natural Resources, Mining & Metals, Utilities or Power) - with hands on experience handling data driven decisions.

  • Experience in consulting or relevant client facing engagements.

  • Ability to think creatively to solve real world business problems.

  • Ability to work in a global collaborative team environment

  • Experience leading or collaborating with a team of data scientists in developing and delivering machine learning models that work in a production setting

  • Candidates with experiences in one or more following areas, acquired through a combination of courses, academic projects and/or industrial projects, are strongly preferred:

    • Scientific AI/ML such as data-driven modeling, digital twins, reduced-order models (ROMs), and physics-informed neural networks (PINNs)

    • Deep reinforcement learning such as value-based algorithms (DQN...), policy gradients algorithms (A3C, DDPG, PPO...), model-based RL and various model-free algorithms.

    • Deep generative models such as Autoregressive, VAEs, GANs, score-based models, diffusion models.

    • Control theory and its applications such as Model Predictive Control and Kalman Filters

    • Advanced simulation of industrial process and physical systems.

    • Optimization such as linear, nonlinear, and mixed-integer programming.




This role is based in Andover MA and will be Hybrid onste 2-3 days per week.

Why us?

At Schneider Electric we're committed to creating a workplace that gives you not just a job but a meaningful purpose in joining our mission to bring energy and efficiency to enable life, progress and sustainability for all.

We believe in e mpowering our team members to reach their full potential, fostering a sense of ownership in their work.

We embrace inclusion as a fundamental value, ensuring that every voice is heard and valued. We value differences, and welcome people from all walks of life. We believe in equal opportunities for everyone, everywhere.

If you want to be part of a company where your contributions truly matter, where you are empowered to make a difference and where inclusivity is valued, we would love to hear from you.

Discover your M eaningful, Inclusive and Empowered career at Schneider Electric.

€34.2bn global revenue
+12% organic growth
135 000+ employees in 100+ countries
#1 on the Global 100 World's most sustainable corporations

You must submit an online application to be considered for any position with us. This position will be posted until filled

Schneider Electric aspires to be the most inclusive and caring company in the world, by providing equitable opportunities to everyone, everywhere, and ensuring all employees feel uniquely valued and safe to contribute their best.

We mirror the diversity of the communities in which we operate and we 'embrace different' as one of our core values. We believe our differences make us stronger as a company and as individuals and we are committed to championing inclusivity in everything we do. This extends to our Candidates and is embedded in our Hiring Practices.

You can find out more about our commitment to Diversity, Equity and Inclusion here and our DEI Policy here

Schneider Electric is an Equal Opportunity Employer. It is our policy to provide equal employment and advancement opportunities in the areas of recruiting, hiring, training, transferring, and promoting all qualified individuals regardless of race, religion, color , gender, disability, national origin, ancestry, age, military status, sexual orientation, marital status, or any other legally protected characteristic or conduct.The AI Industry Researcher will be working with the Strategy and Innovation AI Research team to identify, evaluate and develop advanced Analytical, Machine Learning and AI Solutions for Schneider Electric's AI HUB and its internal and external customers. The core challenges will be to identify and develop strategic, innovative and disruptive solutions for Schneider Electric and its customer by leveraging the Schneider DNA and cutting-edge AI/ML technologies.

Key Responsibilities:


  • Take ownership for an entire project workstream or work with your colleagues jointly on a bigger project.

  • Provide AI Research Services to Schneider Electric Business, Clients and Partners

  • Develop Next Generation AI and Data Products together with Schneider Electric Clients and Partners

  • Research and survey industrial reports and technical papers on latest industrial trends, case studies, models and methodologies in the areas of team's research.

  • Successfully develop, conceptualize and test various statistical, AI and machine learning solutions to solve the future challenges.

  • Integrate the outcomes into the existing Schneider EcoStruxure Landscape to elevate Schneider Electric's ability to create value for clients in areas and through means not immediately apparent to clients

  • Researches, develops and maintains machine learning and statistical models for business requirements.

  • Partners with lines of business to translate business analytic problems into technical solutions and actionable recommendations across the organization

  • Work across the spectrum of statistical modelling including supervised, unsupervised, & deep learning techniques to apply the right level of solution to the right problem

  • Build frameworks leveraging APIs to industrialize AI models across the organization

  • Coordinate with different functional teams to monitor outcomes and refine/ improve the machine learning models

  • Build frameworks leveraging APIs to industrialize AI models across the organization

  • Collaborate with data and software engineers to enable deployment of models that will scale across the company's ecosystem

  • Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown)


AI Industry Researchers in Data and AI projects following state-of-the-art approaches for project execution from adapting existing assets to Analytics use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases, and engaging in fundamental research to develop novel solutions.





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