The Professional Services team within Data & Performance works hand in hand with the various entities of Schneider Electric, to :
Understand SE entities demands provide guidance, prioritize and orchestrate delivery in the Data & Performance Porfolio based on use case;
Deliver Reusable Data Objects that can be leveraged at global and local levels for any BI & Analytics needs;
Deploy the Data Franchise program to increase data maturity of all SE entities and operate under one common governance;
Within this team, you would work with internal business to define data critical elements, run data quality tasks like data profiling & analyze the results in order to report to business / agile team any findings and ensure global database enhancement.
1 / Analyze complex datasets from multiple sources
2 / Compose reports and analysis
3 / Crunch data to detect potential issues
4 / Work closely with Analytics Team to ensure our data warehouse fits the business requirements
5 / Follow-up data quality issue resolution with accountable teams.
MSC degree in IT Management, Mathematics, Statistics, Management Engineering, Applied Mathematics, Economics, Computer Science, Computer Engineering or Information Systems
Master’s degree with a minimum of 2 years of relevant experience (OR Bachelor's degree with a minimum of 5 years of relevant experience) in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
Technical Field :
Good working knowledge of Microsoft Office, especially Excel. Basic knowledge of technical databases (e.g. SQL language, Oracle, Amazon Redshift).
Knowledge and experience with the following tools is a plus : Alteryx / Tableau / Power BI / / ERP / CRM
Qualifications (Required) :
At least 1 years work experience in Business Analysis, Predictive Analytics and Data Visualization (2 years preferred)
Must be familiar with Statistical Analysis, Modeling and machine learning methods (time series analysis, experiment design regression, classification,and clustering, etc.)
A strong knowledge of statistics and data analysis with experience in machine learning techniques.
SQL experience which includes database design, manipulation, and querying
Familiarity with large datasets, understanding of data analysis workflows and frameworks
Fluency in a programming language (Python, C, C++, Java, SQL)
Proficient with common data science toolkits, such as Alteryx, TensorFlow, Rapid Miner
Working knowledge of statistics, machine learning algorithms such as Random Forest, Support Vector Machine, Neural Networks, etc.
and / or Natural Language Processing techniques.
Experience with visualization software / tools such as Spotfire, Tableau, Power BI, etc.
Knowledge in Big Data Platforms such as Hadoop, Spark, Hive, Redshift and NoSQL systems
Familiarity with cloud technologies such as AWS, Microsoft Azure, etc.
Proven project management skills
Excellent communication, presentation, and writing skills to effectively relate technical terms to business terms
Strong logical, problem solving, and decision-making skills
Qualifications (Preferred) :
Implemented projects using Statistical Analysis and / or Advanced Analytics modeling
Implemented projects using Big Data Platforms such as Hadoop, Spark, Hive, Redshift and NoSQL systems
Certified Analytics Professional
Experience with software engineering, database administration and cloud technologies