As part of our Dublin based Data Hub the Data Scientist will be responsible for designing and executing processes related to predictive / analytical modelling, data mining, and research on large scale.
The Data Services Group sits within TIS (Technical Infrastructure Services) providing a real-time, agile Enterprise Data Platform. We provide traditional Relational Database support and consultation alongside Data Analytics, In-memory, Virtualisation, Big Data built on a Self-service and automation platform. We also provide services around Data Security, Data Quality and the full Lifecycle management.
Purpose of your role
The Data Scientist will be responsible for designing and executing processes related to predictive / analytical modelling, data mining, and research on large scale, complex data sets, using statistical, machine learning, graph modelling, text mining and other modern techniques. This individual will also be responsible for collaborating with various teams, and provide periodic updates through presentations and prototype demonstrations.
The key responsibilities of this role are:
- Support and delivery of assigned project work.
- Pro-active detection and timely escalation of any issues.
- Driving root cause analysis and resolution to closure.
- Identification and driving of related service quality improvements and engineering deliverables.
- Escalation as necessary to secure assistance and technical guidance from other Technology teams to resolve support issues.
- Management and progression of Action items.
- Automation and process improvement.
Experience and Qualifications Required
- Ph.D. or Masters in mathematics or statistics or computer science or operations research or a related field.
- Typically requires 5 to 7 years of experience in solving complex analytical problems using quantitative techniques that comprises of analytical, mathematical and technical skills.
- A good team worker.
- Ability to prioritize and co-ordinate activities.
- Experience of working under tight deadlines on a regular basis.
- Good analytical, problem solving and documentation skills.
- Ability to adapt to changing business needs (flexible) and learning new skills quickly.
- Good written and verbal communication skills, together with the ability to communicate complex quantitative analysis in a clear, concise and actionable manner with management and other business and technical groups.
- Calm approach when under pressure.
- Customer focused - strong service ethic.
- Ability to work on own initiative with minimal direction.
- Hands on analytics professional with the ability to conceptualize, architect and design, develop and implement solutions for complex business problems.
- Should be proficient in conducting advanced data analysis and applying advanced statistical and predictive modeling techniques to build, maintain and improve on multiple real-time decision systems.
- Should have experience in using Machine Learning algorithms and business visualization
- Should have experience in handling large, complex, multi-dimensional datasets including structured, unstructured, real time and social data
- Should have very good knowledge and experience in big data technologies - Hadoop, Spark, Kafka, flume, Hive, Impala etc.
- Should have strong programming skills in R, Python, SAS, SQL and NoSQL databases.
- Should have experience handling large and complex analytics assignments as lead data scientist
- Exposure to Cloud technologies
- RDBMS technologies such as Oracle, SQL Server