Senior Data Scientist

The Senior Data Scientist will be responsible for the following:

• Advanced Analytics and Model Development: Design develop and deliver sophisticated data products including problem definition data acquisition data exploration and visualization feature engineering algorithm experimentation machine learning model development evaluation and deployment.
• Innovation and Prototyping: Drive innovation by rapidly prototyping proofofconcept ideas and converting them into enterprise solutions.
• Large Language Models (LLMs): Develop and implement advanced LLMs for various applications enhancing the companys capability in natural language processing and understanding.
• Forecasting: Implement advanced forecasting techniques to predict future trends and behaviours providing valuable insights for decisionmaking.
• Customer Lifecycle Management: Analyse customer data to optimize customer lifecycle management strategies enhancing customer engagement and retention.
• Intelligent Products: Develop intelligent products that leverage AI and machine learning to deliver enhanced customer experiences and operational efficiencies.
• Stakeholder Management: Produce detailed reports and presentations to effectively communicate findings and recommendations to stakeholders at various levels.
• Infrastructure Management: Oversee the management and optimization of our AWS infrastructure to ensure robust scalable and costeffective data solutions.
• Mentorship and Team Development: Mentor junior data scientists fostering a culture of continuous learning and professional growth within the team.

Team Working

• Actively contribute to the Data Science team dynamics and improvements.
• Engage in internal Business Intelligence and Analytics communities to share knowledge and improve team processes.
• Provide regular and accurate reports of progress to technical leads and the Project lead where required.
• Build strong relationships with stakeholders to provide highvalue solutions within the business while keeping communication channels open.
• Maintain strong technical awareness and familiarity with new and upcoming technologies around Data Integration and Business Intelligence Analysis.
• Be prepared to give presentations or provide mentoring on any new technology or skills acquired in a collegiate environment.
• Stay abreast of industry trends and participate in external communities to keep uptodate and offer informed positions when defining or consulting on solution design.
• Knowledge:
  
  • Extensive knowledge of data science techniques including data preparation exploration and visualization.
    
  • Indepth understanding of data mining techniques in one or more areas of statistical modelling methods time series text mining optimization information retrieval.
    
  • Proven ability to produce workflows using classification clustering regression and dimensionality reduction.
    
  • Expertise in prototyping and applying statistical analysis and modelling algorithms to solve complex problems in new domains.
    
  Qualifications
  
  • Bachelors or masters degree in computer science Data Science Machine Learning or a related field. Ph.D. is a plus.
  • 5 years of experience in machine learning data science or related roles with a strong track record of developing Data Science powered data products in an agile environment.
  • Proficiency in programming languages such as Python R with a focus on machine learning libraries and frameworks (e.g. TensorFlow PyTorch scikitlearn).
  • Extensive experience with SQL and related relational databases.
  • Strong understanding of statistical analysis data mining and predictive modelling techniques.
  • Excellent problemsolving skills and the ability to think critically and creatively.
  • Strong communication and collaboration skills with the ability to work effectively in a teamoriented environment.
  • Proven ability to manage business stakeholders translate business needs into technical requirements and deliver impactful solutions.
  • Experience with version control systems (e.g. Git) and agile development methodologies.
    
  Preferred Qualifications
  
  • Experience of working on projects centred around Forecasting Customer Lifecycle Management and Dynamic Pricing.
  • Experience of taking projects from prototype to delivery stages while operating in agile development methodologies.
  • Experience of working with AWS Technologies Storage (RDBMS S3 Redshift etc.) Compute (EC2 Lambda Kinesis EMR etc.) and Data Science related managed services (Sagemaker AWS Forecast Bedrock etc.).
    
  
  
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