Essential Skills
Enthusiasm for building analytics & data science solution, keeping up with latest trends
Analytical mindset and experience in building Data Science solutions.
Experience in solving business problems using Data.
Strategic Mindset with a Customer Focus
Ability to articulate complex issues and desired outcomes of analytical output
Proven analytical skills and evidence-based decision making
Excellent problem solving, troubleshooting & documentation skills
Excellent written and verbal communication skills
Excellent collaboration and interpersonal skills
Ability to innovate, adapt and grasp new skills and content
Ability to work closely with key stakeholders and build collaborative partnerships
Ability to share complex data & Data science approach with business stakeholders
Ability to self-manage tasks aligning with business outcome.
Proactively gathering feedback and continuously improving
Proven ability to experiment with different Data Science packages to deliver business value.
Ability to modify data science solution based on enterprise technology stack
It is expected that the role holder will most likely have the following qualifications and experience
15+ years' experience leading Machine learning engineers, Data Scientists
Lead teams to build and deploy machine learning models to achieve business outcomes.
Proficient users in SQL, Python, PySpark, Spark ML language.
Good understanding of cloud platforms such as Databricks (preferred), AWS, Azure or GCP.
Proficient in source code controls using GitHub.
Highly developed data analytic skills, working with structured, semi-structured unstructured datasets
Experience is using different data science packages to solve business problems.
Good understanding of customer data, digital data, data science landscape
Ability to provide data-driven insights to support decision making or improve customer experience.
Explore new methodologies to solve business problems in a collaborative way.
Strong stakeholder management and influencing skills to shape the Data Science backlog with stakeholders.
Strong communications skills, able to convey complex messages simply and effectively.
Ability to visualise data with different data visualisation tools to share insights with stakeholder.
Lead the use of Data Science techniques across marketing to provide data-driven insights and support strategic decision making across teams.
Accountable for identifying, embedding, promoting, and ensuring continuous improvement within the use of new data and advanced analytics across the teams.
Present analytical findings using data visualisation tools and creation of insight presentations for various audiences.
Development of new or improved analytic techniques to support customers met and un-met financial needs.
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