Our partner T-Systems is looking for a Data Scientist.
Potential end: 31.8.2019, possibility of extension for another 12 months
Number of man days (hours) per person: 40 MD
Number of needed profiles: 1 profile
Place of work: preferably onsite, agreement possible
Key player in group-wide top projects in the field of data analytics; from the demand management to proof-of-concept and go-live.
Evaluate, develop and maintain data analytics applications and customer solutions in Finance and other domains in cooperation with domain experts and Data Engineers.
Design and recommend solutions for a variety of data-driven business demands and present the results on management level.
Apply appropriate statistics, machine learning and analytical approaches in the development of business solutions.
Design and implement statistical data quality procedures for new data sources.
Support proof-of-concepts in state-of-the-art data analytics environments to show feasibility and develop solutions for data related business demands.
Support our finance division in customer workshops and discussions to specify appropriate approaches, methods, tools and solutions.
Monitor the Data Scientists in the team from a technical point of view.
One of the experts in the group-wide data science community and provide new impulses as well as best practices.
Bachelor, Master or PhD degree in Mathematics, Statistics, Physics, Computer Science or Data Science or equivalent education.
PhD degree in the context of Machine Learning or Artificial Intelligence is beneficial.
At least 8 years of relevant work experience.
Proven experience in developing algorithms and implementing data analytics solutions in agile big data projects in which you play a leading role; ideally in an international context.
Profound knowledge in mathematics, statistical methods and machine learning principles as well as experience in two of the following methods: clustering, classification, modeling, regression, text analysis, pattern recognition, neuronal networks.
Areas of experience: Finance analytics, time series analytics, social media analytics, location data analytics, security data analytics, customer data analytics, signal processing, anomaly detection.
Knowledge of data analytic tools (Knime, Rapidminer, Talend, Tableau, Cassandra, Hadoop, Spark) and design and manage big data environments, evaluate and configure components, adapt and code algorithms for customer solutions.
Familiar with open/private cloud technologies as well as other cloud solutions such as Microsoft Azure, SAP HANA.
Agile working mode should not be a strange word to the candidate.
Excellent written and verbal communication competences in English (German optional).