Lead/Sr. Lead Data Science & AI

2 Months ago • All levels • Data Analysis

Job Summary

Job Description

As a Director, Data Science & AI, you will be responsible for formulating business problems into data science solutions, validating OKRs against statistical measures, and performing data wrangling. You will be expected to excel in data storytelling, problem-solving, and possess strong business acumen. Key responsibilities include autonomous task execution across platforms, making informed decisions, optimizing processes through real-time analytics, managing knowledge, interacting with users, and continuously learning. The role requires proficiency in Natural Language Understanding and Generation, autonomous workflow management, API integration, real-time analytics, and reinforcement learning. Preferred knowledge domains include business operations, customer service, technical documentation, and organizational policies. Performance will be measured by task completion rates, decision quality, user satisfaction, and learning adaptability.
Must have:
  • LLM application development and fine-tuning
  • Agentic AI frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel)
  • RAG patterns and enterprise knowledge integration
  • Prompt design, tool integration, and orchestration
  • Autonomous Task Execution
  • Decision-Making
  • Process Optimization
  • Knowledge Management
  • Customer Interaction
  • Learning & Adaptation
  • Compliance & Ethics
  • Natural Language Understanding and Generation
  • Autonomous Workflow Management
  • Integration with APIs, databases, and enterprise tools
  • Real-time analytics and decision-making
  • Reinforcement learning or feedback-based adaptation
  • Problem Formulation
  • Data Wrangling
  • Data Storytelling & Insight Generation
  • Problem Solving
Good to have:
  • Business operations (sales, marketing, HR, finance)
  • Customer service and support
  • Technical documentation and product knowledge
  • Organizational policies and compliance frameworks
  • Excel VBA
  • Data Curiosity
  • Technical Decision Making
  • Communication & Articulation: Vocal & Written
  • Business Acumen
  • Design Thinking
  • Data Literacy

Job Details

Director, Data Science & AI

Primary Skills

    • Problem Formulation (Business problem to Data Science Problem), OKR Validation against statistical measures, Data Wrangling, Data Storytelling & Insight Generation, Problem Solving, Excel VBA, Data Curiosity, Technical Decision Making (How many iterations to go for vs when to stop iterating), Communication & Articulation: Vocal & Written, Business Acumen (Consume new domains quickly to learn through data), Design Thinking, Data Literacy

Specialization

    • Data Science Foundation: Senior Data Scientist

Job requirements

    • Mandatory skills
    • • LLM application development and fine-tuning
    • • Agentic AI frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel)
    • • RAG patterns and enterprise knowledge integration
    • • Prompt design, tool integration, and orchestration
    • Roles and Responsibilities
    • Key Responsibilities
    • Autonomous Task Execution: Initiate and complete multi-step tasks across platforms (e.g., CRM, ERP, cloud services).
    • Decision-Making: Analyze data and make informed decisions aligned with organizational goals.
    • Process Optimization: Identify inefficiencies and propose improvements using real-time analytics.
    • Knowledge Management: Research, synthesize, and present information to support strategic initiatives.
    • Customer Interaction: Engage with users via chat, email, or voice to resolve queries and escalate issues when necessary.
    • Learning & Adaptation: Continuously improve performance based on feedback and outcomes.
    • Compliance & Ethics: Operate within defined ethical, legal, and organizational boundaries.

    • 🧩 Required Capabilities
    • Natural Language Understanding and Generation
    • Autonomous Workflow Management
    • Integration with APIs, databases, and enterprise tools
    • Real-time analytics and decision-making
    • Reinforcement learning or feedback-based adaptation

    • 📚 Preferred Training Data / Knowledge Domains
    • Business operations (sales, marketing, HR, finance)
    • Customer service and support
    • Technical documentation and product knowledge
    • Organizational policies and compliance frameworks

    • 📈 Performance Metrics
    • Task completion rate and accuracy
    • Decision quality and impact
    • User satisfaction scores
    • Learning velocity and adaptability
    • Ethical compliance rate
₹0 - ₹0 a year
Not a Bar for right fit!!

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