Data Scientist, Data Center Systems

Job description

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: https://youtu.be/NlLJMv1Y7Hk .

Great people make Schneider Electric a great company.

What do you get to do in this position?

Summary of Job:

The Data Scientist within Data Center Systems Global LOB will collaborate with the CTO Data Science Team and LOB offer and technical teams to build, test and deploy data-driven models for our products, systems and services.

Our data science efforts are interdisciplinary – incorporating understanding and methodology from engineering, computer science, statistics, operations research, machine learning, and artificial intelligence. The Data Scientist will design and validate models in Python and R utilizing data from Schneider Electric repositories and laboratories -- and external sources.

Additionally, the Data Scientist will work with and alongside engineering and services stakeholders to identify business opportunities, use cases, and new data sources. Communication and leadership skills will be critical as you will serve as a technical resource for data science for internal projects and external collaborations and partnerships

Essential Functions:

• Business Requirements - Work with Data Center Systems stakeholders to identify the business requirements and the expected outcome. Model and frame business scenarios that are meaningful and which impact on critical business processes and/or decisions.

• Data Requirements - Identifies what data is available and relevant, including internal and external data sources, leveraging new data collection processes. Collaborate with subject matter experts to select the relevant sources of information and work to support data collection, integration, and retention requirements based on the input collected with the business.

• Analysis - Solve analytics problems and communicate results and methodologies. Work in iterative processes with SMEs and validate findings. Develop experimental design approaches to validate finding or test hypotheses. Employs the appropriate algorithm to discover patterns.

• Qualification and Assurance – Assess with the LOB, the expected qualification and assurance of information in the support of the use case. Defines the validity of the information, how long the information is meaningful, and what other information is it related to.

• Access Management & Control – Works with the data steward to ensure that the information used is in compliance with the regulatory and security policies in place

• Quantification – Identifies and analyzes patters in the volume of data supporting the initiative, the type of data and the speed or sudden variations in data collection

• Policies, standards and procedures – Partners with the data stewards to define the data quality expectation in the context of the specific use case.

• Communications – Presents and depicts the rationale of their findings in easy to understand terms for the business

• Change advocacy – Educates the organization on new approaches, such as testing hypotheses and statistical validation of results. Helps the organization understand the principles behind findings to drive organizational buy-in.

• Metrics – Demonstrates clarity, accuracy, precision, relevance, depth, breadth, logic, significance and fairness.

Desired profile

Qualifications :

This job might be for you if:

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related technical degree

• Demonstrated data science expertise and consultative approach

• Experience with Technical programming desirable (particularly coding in R, Python, or MATLAB)

• Self-managed, disciplined and committed to working in a fast-paced environment

• Good written and verbal communication skills

• Excellent problem-solving skills and systems thinking

• Strong interpersonal skills and ability to work effectively in a team environment