AI Industry Consultant at SCHNEIDER ELECTRIC SMART GRID SOLUTIONS LLC

Grenoble, Auvergne-Rhône-Alpes, France -

Full Time

Start Date

Immediate

Expiry Date

14 May, 26

Salary

0.0

Posted On

13 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Artificial Intelligence, Machine Learning, Deep Learning, Data Strategy, Statistical Modelling, Supervised Learning, Unsupervised Learning, Cluster Analysis, Neural Networks, Bayesian Models, Genetic Algorithms, Fuzzy Logic, Python, R, TensorFlow, API Frameworks

Industry

Automation Machinery Manufacturing

Description

Schneider Electric’s purpose is to empower all to make the most of our energy and resources, bridging progress and sustainability for all. At Schneider, we call this Life Is On. We are driving digital transformation by integrating the most advanced energy and automation technologies. We connect products, control platforms, software and services throughout the lifecycle of our customers' activities to the cloud for integrated management of residential housing, commercial buildings, data centers, infrastructures and industries. Artificial intelligence has the potential to transform industries and help unlock efficiency and sustainability. You' re interested in solving real world problems with AI? Join our AI Hub to create a sustainable, digitized, new electric future. We combine our long-standing manufacturing and domain expertise with cutting-edge innovation in AI, machine learning, and deep learning to empower smarter decision-making, agility, and decarbonization. The AI Industry Consultant will be working with the New Value Streams team to identify, evaluate and develop advanced Analytical, Machine Learning and AI Solutions for Schneider Electric’s AI HUB and its clients. The core challenges will be to find creative solutions for Client Challenges by leveraging the Schneider DNA and the wealth of methodologies from the AI/ML World. Responsibilities: Take ownership for an entire project workstream or work with your colleagues jointly on a bigger project. Provide AI Consulting Services to Schneider Electric Clients and Partners Develop AI and Data Strategies together with Schneider Electric Clients and Partners Successfully develop, conceptualize and test various statistical, AI and machine learning solutions to solve the challenge at hand 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 Consultants 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: Masters or Ph.D. (Computer Science, Statistics, Engineering, Physics, Mathematics, Economics) Minimum 3 years of Data Science experience for Ph.D. candidates and 5 years for master’s candidates Minimum 3 years of work experience in relevant domains (Energy, Oil & Gas, Chemicals, Natural Resources, Mining & Metals, Utilities or Power) – with hands on experience handling data driven decisions 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, Deep Learning, Genetic Algorithms, Fuzzy Logic, Inference Systems 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 of 3 years of experience in consulting or relevant client facing engagements Minimum 3 years of experience in statistical software - Python, R, Octave, TensorFlow, Caffe or Theano) Minimum 3 years of programming experience (Python, R or similar) Preferred Qualifications: AI and Data Consulting field experience Familiarity with relational databases and intermediate level knowledge of SQL 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 Knowledge of UNIX or Linux environments Experience working with large data sets and tools like MapReduce, Hadoop, Hive, etc. Experience working with large data streaming technologies like Spark, Flink, etc. Familiarity with relational databases and intermediate level knowledge of SQL Proficient verbal and written communication skills in English

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Responsibilities

The consultant will identify, evaluate, and develop advanced Analytical, Machine Learning, and AI Solutions for the AI Hub and clients, taking ownership of project workstreams or collaborating on larger projects. Key duties include providing AI consulting services, developing AI/Data Strategies with clients, and integrating outcomes into the EcoStruxure Landscape.