Full-Time

Data Science Lead

Zensar

Zensar

No salary listed

India

In Person

Category
Data & Analytics (1)
Required Skills
LLM
Data Science
Machine Learning
Data Analysis
Requirements
  • Relevant degree or qualification.
  • Extensive experience in data mining, modelling, and analytics.
  • Deep knowledge of AI and machine learning techniques
  • Experience with large language models (LLMs) and prompt engineering
  • Sound knowledge of data analytics and reporting tools.
  • Strong understanding of data models and architecture.
  • Ability to integrate traditional research and insight with data.
  • Proven track record of putting analytical products into production
Responsibilities
  • Gather data and enable a centralized data knowledge management system that integrates sources into one platform
  • Develop a process to aggregate data and then enable centralization
  • Mine and analyse large sets of data to derive actionable insights and value from data
  • Develop an approach and model for foresight generation
  • Perform predictive analytics and data modelling to derive insights about future business decisions that improve customer experiences and business revenue
  • Design, implement, and support the delivery of data solutions
  • Assess the effectiveness and accuracy of new data sources and data-gathering techniques
  • Develop analysis metrics and new reports to support critical business decisions
  • Provide input on optimal data architecture to support effective data solutions
  • Develop relevant data models, including statistical and machine learning models, to derive more value from data
  • Guide data types and content that should maximize value
  • Collaborate with stakeholders to understand current challenges and needs that should be met with data solutions
  • Identify data tasks and processes that can be improved and automated
  • Develop real-time data gathering, analytics, and reporting capabilities
  • Launch performance dashboards
  • Enable automation
  • Integrate with data roles to ensure a holistic GMPAS overview
  • Develop and deploy AI and machine learning models
  • Work with large language models (LLMs) and prompt engineering
  • Put analytical products into production environments
  • Manage own performance
  • Plan work over the applicable period
  • Mentor and guide junior data scientists and analysts
  • Understand, interpret and implement COE specific compliance requirements within GMPAS delivery e.g. POPI

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