AI Industry Lead Consultant

Overview

Schneider Electric’s purpose is to empower all to make the most of our energy and resources, bridging progress and sustainability for all. We call this Life Is On and are developing a distributed global AI Hub between the United States (Boston), India (Bangalore) and France (Paris/Grenoble) to deliver innovative AI projects at scale. The AI Industry Lead Consultant will work 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.

Responsibilities

• Lead an Industry Segment Team of AI Industry Consultants, including team management, development, and research & career development.
• Provide AI consulting services to Schneider Electric clients and partners.
• Develop AI and data strategies with clients and partners.
• Develop, conceptualize and test various statistical, AI and machine‑learning solutions to solve challenges.
• Integrate outcomes into the existing EcoStruxure Landscape to create value for clients.
• Research, develop and maintain machine‑learning and statistical models for business requirements.
• Partner with business lines to translate analytic problems into technical solutions and actionable recommendations.
• Work across supervised, unsupervised and deep‑learning techniques to apply the right solution to the right problem.
• Build frameworks leveraging APIs to industrialize AI models across the organization.
• Coordinate with functional teams to monitor outcomes and refine or improve models.
• Collaborate with data and software engineers to deploy models that 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).
• Lead AI Industry Consultants in data and AI projects, following state‑of‑the‑art approaches for project execution.

Qualifications

• Masters or Ph.D. in Computer Science, Statistics, Engineering, Physics, Mathematics, or Economics.
• Minimum 7 years of data science experience for Ph.D. candidates and 9 years for master’s candidates.
• Minimum 7 years of work experience in relevant domains (Energy, Water & Wastewater, Mining, Metals & Minerals, Consumer Packaged Goods) with hands‑on experience handling data‑driven decisions.
• Minimum 7 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 7 years of experience in various statistical and machine‑learning models, data mining, and unstructured data analytics in corporate or academic research environments.
• Minimum of 7 years of experience in consulting or client‑facing engagements.
• Minimum 5 years of experience in statistical software (Python, R, Octave, TensorFlow, Caffe, or Theano).
• Minimum 5 years of programming experience (Python, R or similar).

Preferred Qualifications

• AI and data consulting field experience.
• Familiarity with relational databases and intermediate 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 production‑ready machine‑learning models.
• Knowledge of UNIX or Linux environments.
• Experience working with large datasets and tools such as MapReduce, Hadoop, Hive, etc.
• Experience working with large data‑streaming technologies such as Spark, Flink, etc.
• Proficient verbal and written communication skills in English.