Data Science Lead

Job description

 As a Data Science Engineering Lead you will be the one who is providing technical leadership and also be a main point of contact for design, development, delivery of visualisations, alerts and reports. This all for full stack observability, enterprise search, PAM and SIEM. Together with your team you will have great opportunity to use data science methods to generate insights from large datasets (comprised of syslog, application log, application performance metrics etc).

Our client is one of the world's largest and most respected financial institutions, with 329 years of success, quality and innovation behind us. 

What will you be doing?

• You will be accountable for the successful execution of the roadmap & contribute to the multi-year product strategy and product roadmap that aligns to the business strategy
• Leading the design and delivery of data solutions required for correlating logs & metric data received from different IT stack of a service into a single correlated view
• Delivering solutions to reduce alert noise and aid automated root cause analysis
• Generating strategic insights from large scale datasets through the intelligent application of a broad range of advanced quantitative analytical and statistical techniques
• Using machine learning and algorithmic learning to provide proactive alerting and capacity projections
• Building visualisations, dashboards and reports to meet application teams observability requirements

What we’re looking for:
• Exceptional ability to extract strategic insights from large data sets
• Ability to understand and translate the pattern recognition, exploration of the data, machine learning and algorithmic learning
• Solid understanding of complex enterprise organisational infrastructure and architecture environments
• Excellent communication, engagement, documentation and governance skills

Skills that will help you in the role:
• Proficiency in Python to develop and review code with members of the team
• Experience in delivering complex data science projects
• Extensive experience of statistical analysis, data mining and visualisation techniques
• Experience in cloud platforms such as AWS, Azure, OpenShift or Kubernetes is an advantage

 

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