Data Scientist at ENGIE

Responsibilities   

Data Mining (20%): 

• Design and implement robust data mining models to support analytics and reporting requirements. 
• Carry out pre – processing, cleansing, and validating the integrioty of data to be used for analysis 
• Enhance data collection procedures to include all relevant information for developing analytic systems. 

Statistical modelling (70%) 

• Use statistical and machine learning techniques to develop solutions to support business operations from sales to credit collection. 

Stakeholder management (10%) 

• Communicate results with stakeholders within the business operations teams. 

Experience:  

• 5+ years of industry experience working on data scientist with a focus on data modelling, stakeholder management and data mining.,  
• Proficiency using machine learning frameworks like keras, pytorch, Tensorflow, sckit-learn, statistical tools (statistical tests, distribution, regression, maximum likelihood estimators, strong math skills (multivariate calculus, linear algebra), machine learning methods (k-Nearest Neighbours, Naive Bayes, SVm, Decision forests), Data visualization tools (matplotlib, d3.js, Tableau). 
• Experience working with structured and unstructured data using Python, R, Scala, Java, SQL in addition to one or more of Spark/Hadoop/Hive/HDFS , Apache Airflow, RabbitMQ/Kafka, Spark, Kubernates, and dbt. 
• Working knowledge of databases, data systems, and analytics solutions, including proficiency in SQL, NoSQL, Java, Spark and Amazon Redshift  for reporting and dashboard building. 
• Experience with implementing unit and integration testing.