Senior Data Scientist

Sompo Sigorta A.Ş.

We are looking for a high caliber "Senior Data Scientist" to join our Data Analytics Team with the following qualifications and job description:

• Bachelor’s degree in Computer Science, Statistics, Mathematics or Engineering,
• Minimum 5 years of related job experience, 
• Experience on building complex data sets from multiple data sources, both internally and externally,
• Experienced with Statistical Modeling/Machine Learning/Deep Learning techniques,
• Taking end to end ownership of Machine Learning systems - from data pipelines and training to real-time prediction engines,
• Experience on machine learning platforms such as SAS, SPSS/Modeler, Matlab, Knime, Alterix,
• High proficiency in coding languages, including Python and SQL,
• Ability to understand and implement techniques discussed in AI/ML research papers (academic and technical),
• Possession of excellent analytical thinking, problem-solving and self-education skills,
• Possession of open-minded approach,
• Male candidates must have completed military service.

Preferably;

• Understanding of cloud computing platforms and large-scale databases,
• Experience on cloud based machine learning platforms such as Microsoft Azure ML, Amazon ML,
• Experience on NoSQL databases (Hadoop, Spark),
• Experience with question answering, language modeling, information extraction, text classification, text summarization, conversation/dialog, and related NLP applications.

JOB DESCRIPTION

• Producing analytical solutions to the needs of the business unit, 
• Working on data and complex business problems to drive improved risk-and-return business decisions and results by designing, building, and partnering to implement the right models for the right problems,
• Developing analytical models to drive analytics insights,
• Clearly articulating and presenting recommendations to business partners, and influencing future plans based on insights,
• Identifying new areas of data, research and methodology/models that can solve relevant risk-and-return business challenges,
• Collaborating the with team to understand the business’ problems to identify the optimal methodological, and modeling (method+language/platform) approaches,
• Participating in the continuous improvement of data science and analytics.