Role : Data Science and LLM Director
Overview
This combined role leads the organization's data science initiatives with a special focus on Large Language Models (LLMs), generative AI technologies, and intelligent automation. The position requires strategic leadership in data-driven decision making, specialized expertise in implementing cutting-edge AI language models, and proficiency in developing automated solutions to transform business operations and enhance organizational efficiency.
Core Responsibilities
Leadership & Strategy
- Lead and mentor a team of data scientists, ML and Python engineers, and automation specialists, fostering a culture of innovation, collaboration, and continuous learning
- Develop and execute the organization's data science, generative AI, and automation vision, strategy, and roadmap aligned with business objectives
- Identify and prioritize high-impact opportunities where data science, LLMs, and automation can drive business value and operational efficiency
- Partner with senior executives to ensure AI and automation initiatives support broader organizational goals
- Establish governance frameworks, ethical guidelines, and best practices for responsible AI deployment and automated process implementation
- Drive automation strategy to streamline workflows, reduce manual processes, and enhance productivity across data science operations
Technical Direction
- Design scalable data processing pipelines and architecture for analytics, modeling, LLM implementation, and automated workflows
- Oversee the evaluation, fine-tuning, and deployment of large language models for specific business applications
- Drive implementation of data science, LLM, and automation solutions across various business functions including customer service, content generation, knowledge management, and process optimization
- Develop and implement intelligent automation strategies to streamline data workflows, model deployment, and operational processes
- Balance innovation with practicality, selecting appropriate technologies and automation tools based on business needs and ROI
- Guide the integration of LLMs with existing data infrastructure, systems, and automated processes
- Establish automated monitoring using Python , testing, and deployment pipelines for AI/ML models and data science solutions
Applied Data Science
- Lead the development of predictive models, machine learning solutions, and LLM applications
- Ensure data quality and appropriate data management practices across initiatives
- Direct the collection of new data and refinement of existing data sources to improve model performance
- Oversee experimentation and validation processes to evaluate solution effectiveness
- Facilitate the translation of complex analytical findings into actionable business insights
Communication & Education
- Present findings and recommendations to key stakeholders through reports and presentations
- Serve as the organization's point person for generative AI knowledge and applications
- Develop educational resources and training programs to build data science and AI literacy
- Communicate complex technical concepts to non-technical stakeholders in clear, understandable terms
- Prepare white papers, case studies, and other materials showcasing data science and LLM successes
Qualifications, Education & Experience
- Master's or B,tech in Computer Science, Statistics, Mathematics, Data Science, Machine Learning or related quantitative field
- 10+ years of experience in data science, with at least 3+ years focusing on natural language processing or LLMs
- 7+ years of experience managing technical teams and leading complex projects
- 5+ years of hands-on experience in automation, process optimization, and workflow automation tools
- 8+ years of advanced Python programming experience, including data science libraries, automation frameworks, and ML/AI development
- Demonstrated success implementing data science and automation solutions that deliver measurable business impact
- Experience with large language model deployment, fine-tuning, and evaluation
- Proven track record in developing and implementing automated data pipelines, ML model deployment, and intelligent process automation using Python
Technical Skills
- Expert-level programming skills in Python and proficiency with data science/ML libraries
- Strong background in machine learning, deep learning, and statistical analysis
- Hands-on experience with LLM frameworks such as PyTorch, TensorFlow, or Hugging Face
- Experience with MLOps and the automation of model training, evaluation, and deployment
- Proficiency with cloud platforms (AWS, GCP, Azure) and big data technologies
- Knowledge of data visualization tools and techniques for effective communication
Leadership & Soft Skills
- Strategic thinking and business acumen with ability to align technical solutions to business needs
- Exceptional communication skills for conveying technical concepts to diverse audiences
- Experimental mindset with ability to balance innovation with practical implementation
- Strong project management capabilities and experience with agile methodologies
- Collaborative approach to working with cross-functional teams and stakeholders
Key Performance Indicators
- Development and execution of data science and LLM strategy with measurable business impact
- Successful implementation of LLM-powered solutions that improve operational efficiency
- Quality and effectiveness of data science team output and deliverables
- Adoption of data-driven decision making across the organization
- Creation of scalable, sustainable data science and AI infrastructure
