Research Data Scientist (Finance)

The Research Data Scientist (Internally titled: Lead Data Scientist) 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 time horizon for the Research team is forward focused between 12 and 18 months. 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.
• Work with Schneider Electric Business Units and Partners on applied AI research or innovation projects.
• 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.
• Researches and develops prototypes and POC machine learning and statistical models for business requirements and transfer the solutions to product teams.
• 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.
• Coordinate with different functional teams to monitor outcomes and refine/ improve the machine learning models.
• Collaborate with solution data scientists and solution architects to enable deployment of models that will scale across the company's ecosystem.
• Work with Solution Data Scientists to upskill the team and transfer knowledge and technology.
• Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown)

Lead Data Scientist in Data and AI projects following state-of-the-art approaches for project execution from adapting existing solutions to new use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases, and engaging in cutting-edge research to develop novel solutions.

Basic Qualifications:

• Master's or Ph.D. in Computer Science, Statistics, Engineering, Physics, Mathematics, Economics.
• Three or more years of AI research experience for Ph.D. candidates and more than 5 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, 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.
• Experience with and knowledge of Microsoft Azure, AWS, or other cloud platforms.
• Strong verbal and written communication skills in English. Ability to communicate complex ideas to people with different levels of technical backgrounds including data scientists, solution architects, product managers and business managers.

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.
• Research experience in leading academic institutions or leading industrial labs.
• 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.
• Experience with agile development process.
• Publication records in leading academic journals.
• Candidates with experiences in one or more of the following, 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), physics-informed neural networks (PINNs).
  • Solving Partial Differential Equations (PDN's) with numerical computational methods such as FEMs/FDMs and Deep Neural Network-based solution architecture such as DeepONet in mechanical, fluid, thermal, electrochemical, computational biology, multi-physics modeling or other fields.
  • Exposure or experience in Lithium-Ion battery modeling approaches such as ECM applying models for example: data-driven modeling and physics-based modeling.
  • Proficiency in scientific and engineering computational software packages such as MATLAB and COMSOL.

Looking to make an IMPACT with your career?

When you are thinking about joining a new team, culture matters. At Schneider Electric, our values and behaviors are the foundation for creating a great culture to support business success. We believe that our IMPACT values - Inclusion, Mastery, Purpose, Action, Curiosity, Teamwork - starts with us.

IMPACT is also your invitation to join Schneider Electric where you can contribute to turning sustainability ambition into actions, no matter what role you play. It is a call to connect your career with the ambition of achieving a more resilient, efficient, and sustainable world.

We are looking for IMPACT Makers; exceptional people who turn sustainability ambitions into actions at the intersection of automation, electrification, and digitization. We celebrate IMPACT Makers and believe everyone has the potential to be one.

Become an IMPACT Maker with Schneider Electric - apply today!

€36 billion global revenue
+13% organic growth
150 000+ 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 'inclusion' is 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.

At Schneider Electric, we uphold the highest standards of ethics and compliance, and we believe that trust is a foundational value. Our Trust Charter is our Code of Conduct and demonstrates our commitment to ethics, safety, sustainability, quality and cybersecurity, underpinning every aspect of our business and our willingness to behave and respond respectfully and in good faith to all our stakeholders. You can find out more about our Trust Charter 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 Research Data Scientist (Internally titled: Lead Data Scientist) 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 time horizon for the Research team is forward focused between 12 and 18 months. 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.
• Work with Schneider Electric Business Units and Partners on applied AI research or innovation projects.
• 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.
• Researches and develops prototypes and POC machine learning and statistical models for business requirements and transfer the solutions to product teams.
• 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.
• Coordinate with different functional teams to monitor outcomes and refine/ improve the machine learning models.
• Collaborate with solution data scientists and solution architects to enable deployment of models that will scale across the company's ecosystem.
• Work with Solution Data Scientists to upskill the team and transfer knowledge and technology.
• Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown)

Lead Data Scientist in Data and AI projects following state-of-the-art approaches for project execution from adapting existing solutions to new use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases, and engaging in cutting-edge research to develop novel solutions.