About Us
Schneider Electric creates connected technologies that reshape industries, transform cities and enrich lives. Our 144,000 employees thrive in more than 100 countries. From the simplest of switches to complex operational systems, our technology, software and services improve the way our customers manage and automate their operations. Help us deliver solutions that ensure Life Is On everywhere, for everyone and at every moment:
Great People Make Schneider Electric a Great Company.
We seek out and reward people for putting the customer first, being disruptive to the status quo, embracing different perspectives, continuously learning, and acting like owners. We want our employees to reflect the diversity of the communities in which we operate. We welcome people as they are, creating an inclusive culture where all forms of diversity are seen as a real value for the company. We're looking for people with a passion for success on the job and beyond.
We are looking for a passionate ML /AI Data Scientist Manager withdemonstrated thought-leadership &proven ability to lead the high impact Data science team for the research and development of Data science and analytics-focused products utilizing cutting edge machine learning, natural language processing, and mathematical techniques to drive powerful business results. You will have the opportunity to sail through the team of wide range of stakeholders and functions to help them discover insights hidden in data sets and enable business to improve and disrupt the traditional outcomes. AI ethics, fairness and secure development practices are also our focus areas.
Responsibilities
- Partners with lines of business to understand business problems, conceptualize and be responsible of successful delivery and productization of AI enabled solutions.
- Build and maintain a high performing team of machine learning and data science researchers & Practitioners. Uphold the Schneider Electric's highest standards and principles in the people management while dealing with the conflicting priorities.
- Coordinate with business teams to monitor outcomes and refine/ improve the machine learning models.
- Help team to Conduct quick POC and idea evaluation by mentoring and guiding data science team in choosing the right machine learning approach.
- Work across the spectrum of statistical modelling including supervised, unsupervised, & deep learning techniques to apply the right level of solution to the right problem.
- Conduct evaluations and assessments of new tools and technologies to ensure that the team stays at the frontier of Analytics.
- Evaluate vendors and commercial solution to support build vs buy decision.
- Track emerging developments w.r.t technology, tools, practices, etc in the open source, data science/machine learning/chatbot domain and leverage same for Schneider Electric
- Inspire team to create IP and publications. Motivate the team to Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown)
Qualifications
Requirements and Skills
- You should have bachelor's or master's degree in computer science, Statistics or Mathematics, Informatics, Information Systems or another quantitative field.
- You should have 3+ years of experience of leading a data science team working in diverse area with multiple stakeholders collaboration.
- You should have 12+ years of experience in solving real life complex business problems using machine learning. Hands-on experience in deploying these machine learning solutions to production is mandatory.
- Strong analytical and critical thinking skills. You should also have a business mindset, swift to identify risk situations and opportunities, and able to generate creative solutions to business problems.
- Effective communication skills (written and verbal) to properly articulate complicated models and reports to management and other IT development partners.
- In-depth understanding and modelling experience in supervised, unsupervised, reinforcement and deep learning models; hands-on knowledge of data wrangling, data cleaning/ preparation, dimensionality reduction is required.
- Knowledge of vector algebra, statistical and probabilistic modelling is highly desirable.
- Exploratory data analysis and hypothesis testing to identify ML opportunities is a plus.
- Experience in major machine learning frameworks such as Pytorch, Scikit-Learn, Tensorflow, Pandas, SparkML etc.
- Fluency in programming skills such as Python, R, or other equivalent languages
- Familiarity with databases likeMySQL, Oracle, SQL Server, NoSQL, etc. is desirable
- Experience working with Amazon SageMaker or Azure ML Studio for deployments is required
Experience in data visualization software such as Tableau, ELK, etc is a plus
Schedule: Full-time
Req: 008XL7
