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Job ID: 34269
Job Openings by Title Senior Data Scientist
Location Germany
Description:
Position:  Senior Data Scientist

Company: Insurance Organization

Location: Germany

Job ID: 34269

Responsibilities:
-Conceive and develop end-to-end, data-driven solutions to support the company’s operational entities
and initiatives. 
-Lead analytics products and data-driven initiatives with a small cross-functional team. Mentor and coach junior data scientists.
-Develop and work on the integration of end-to-end software prototypes, including data engineering, machine learning and artificial intelligence algorithms, or custom algorithm development.
-Strongly contribute in agile cross functional teams, bringing the development skills for robust integration of AI products into technical systems
-Identify opportunities for innovation through analytics in the business of the company. Evaluate potential, scope projects, and define deliverables.
-Measure and track impact of the products developed through business KPIs. Present result of
analyses to business owners and share knowledge with team members. 
-Support the simplification of processes so that business owners, in addition to data scientists, can leverage Big Data to drive business decisions.
-Investigate new data technologies and contribute to the continual development of the Big Data architecture.

Qualifications:
-M.S. or Ph.D. in a relevant technical field such as computer science or engineering. 
-Strong programming experience in Python is required. Experience with R is a plus. Object oriented (java, C++) or functional (Scala) programming languages are a plus. 
-Fluency in English is required, additional languages are a plus.
-Experience with databases and SQL language. 
-Working experience as Data Scientist (3+ years). Experience in leading projects and small,  agile project teams is a strong plus.
-Experience in maintaining ML services/API in production. 
-Software development experience is a strong plus. 
-Experience in manipulating and understanding complex, high-volume data from diverse sources.
-Experience in applying modern machine learning and artificial intelligence models (supervised and unsupervised, such as gradient boosting and deep learning) in a business context.
-Experience with distributed computing is a plus (e.g., Spark, Hadoop, H2O etc.). 
-Ability to relate business problems to data-driven solutions using machine learning and artificial intelligence.
-Ability to communicate complex quantitative analysis in a clear and precise manner to audiences from different departments and at different levels.
-Creative thinking and strong analytical and problem-solving skills.
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