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Senior Data Scientist
4 months ago
Responsibilities
_Data Preparation_
- Assess the effectiveness and accuracy of new Data sources and Data gathering techniques.
- Extend the company's Data with third party sources of information when required.
- Process, cleanse and verify the integrity of Data used for Analysis.
- Identify valuable data sources and Automate collection processes.
- Undertake preprocessing of structured and unstructured data.
_Analysis and Model Building_
- Mine and Analyze data to drive optimization and improvement of Pricing, Product development, Marketing techniques, and business Strategies.
- Analyze large amounts of information to discover trends and patterns.
- Select features, build, and optimize classifiers using advanced Machine learning techniques.
- Utilize predictive Modeling to influence value drivers such as sales, client retention, expense management, and optimization of client experience.
- Blend models through ensemble modeling.
_Stakeholder Engagement_
- Present information using data visualization techniques.
- Propose solutions and strategies to business challenges.
_Implement and Monitor_
- Coordinate with different functional teams to implement models, allowing for different systems integration patterns, and monitor outcomes.
- Develop processes and tools to monitor and analyse model performance and data accuracy.
_Leadership and Team Management_
- Provide leadership and guidance to team members in Advanced Analytics, the Data engineering and Product development teams.
- Collaborate with data and analytics experts to enhance workflow processes, documentation, technical model builds and model deployment
- Support and mentor team members to drive value for the Group.
Requirements:
_Qualifications_
- Degree in Statistics, Actuarial Science, Mathematics, Computer Science or another quantitative field.
- An advanced degree in a quantitative field would be advantageous.
_Experience_
- A proven track record of successfully implementing Datadriven solutions and delivering measurable business impact.
- Demonstrated Leadership and Management abilities: Experience in leading and managing teams, providing guidance and mentorship to junior members, and effectively coordinating with crossfunctional teams.
_Skills/ Knowledge_
- Strategic thinking: A strategic mindset and the ability to align data science initiatives with broader business objectives. Able to identify opportunities for leveraging data and analytics to drive innovation and improve business outcomes.
- Technical Expertise: A deep understanding and expertise in various Data science techniques, Statistical modeling, Machine learning algorithms, and Data mining.
- A thorough knowledge of Programming languages such as Python or R and proficient in querying databases and working with big data tools and frameworks like Hadoop, Spark, or SQL.
- Communication and
Presentation Skills:
Ability to effectively communicate complex data science concepts and insights to both Technical and non-technical stakeholders.
- Excellent presentation skills and the ability to translate datadriven insights into actionable recommendations for business stakeholders.