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Job Title: AI Industry Research Consultant
Company Name: Schneider Electric
Location: Boston, MA
Position Type: Full Time
Post Date: 09/28/2022
Expire Date: 01/15/2023
Job Categories: Computers, Software, Construction, Mining and Trades, Consulting Services, Engineering, Finance/Economics, Information Technology, Military, Science, Quality Control, Research & Development, Environmental, Natural Resources, Energy / Utilities
Job Description
AI Industry Research Consultant

Job Description

The AI Industry Researcher 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 time horizon for the Research team is forward focussed between 12 and 36 months. The core challenges will be to find creative solutions for upcoming Client Challenges by leveraging the Schneider DNA, experimental technologies from the AI/ML methodologies and the wealth of existing methodologies from the AI/ML World. 

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

  • 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 Research 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

Why us?

Schneider Electric is leading the digital transformation of energy management and automation. Our technologies enable the world to use energy in a safe, efficient and sustainable manner. We strive to promote a global economy that is both ecologically viable and highly productive.


€25.7bn global revenue

137 000+ employees in 100+ countries

45% of revenue from IoT

5% of revenue devoted for R&D



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


It is the policy of Schneider Electric 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. Concerning agencies: Schneider Electric does not accept unsolicited resumes and will not be responsible for fees related to such.



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Company Name: Schneider Electric
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