Lead Data Scientist

Role overview

Responsibilities

• check_circle Drive end to end design of Agentic AI solutions that orchestrate autonomous workflows and deliver measurable business outcomes for global stakeholders in a hybrid work environment.
• check_circle Develop robust NLP models that extract insights from large scale multilingual text data to improve decision making and enhance customer experience across multiple channels.
• check_circle Architect and implement open source LLM based solutions that are optimized for latency scalability and cost efficiency while maintaining strong performance on enterprise use cases.
• check_circle Guide design of generative AI applications that create high quality content recommendations and summaries while adhering to responsible AI and data privacy standards.
• check_circle Establish reusable frameworks prompts and evaluation methods that enable teams to rapidly prototype and productize Agentic AI and generative AI capabilities.
• check_circle Coordinate with product managers architects and engineering teams to translate complex business needs into technical AI roadmaps and backlog items with clear acceptance criteria.
• check_circle Review data pipelines feature stores and model serving infrastructure to ensure that AI solutions remain reliable observable and maintainable in production environments.
• check_circle Perform rigorous experimentation benchmarking and error analysis on LLMs and NLP models to continuously improve accuracy robustness and fairness across user segments.
• check_circle Document solution designs experiment findings model cards and operational runbooks in a clear and comprehensive manner to support maintainability and audit readiness.
• check_circle Collaborate with risk legal and compliance partners to embed governance model monitoring and ethical AI practices throughout the solution lifecycle.
• check_circle Mentor senior data scientists and machine learning engineers through code reviews design discussions and knowledge sharing on Agentic AI NLP and LLM best practices.
• check_circle Engage with business stakeholders to explain complex AI behaviors manage expectations and ensure that deployed solutions create transparent value for the organization and society.
• check_circle Evaluate emerging open source LLMs frameworks and tooling to recommend pragmatic adoption paths that align with enterprise security cost and performance requirements.

Basic qualifications

• Exhibit extensive hands on experience in designing and deploying Agentic AI systems that coordinate multiple tools or services to complete complex business tasks.
• Demonstrate strong expertise in modern NLP techniques including transformers semantic search text classification summarization and conversational modeling.
• Show proven track record in implementing and fine tuning open source LLMs using approaches such as instruction tuning parameter efficient methods and retrieval augmentation.
• Apply deep understanding of generative AI concepts such as prompt engineering alignment content filtering and evaluation of generated text for quality and safety.
• Utilize solid programming skills in languages like Python along with experience in machine learning libraries and deep learning frameworks appropriate for large models.
• Employ sound knowledge of data engineering fundamentals including data quality feature engineering and MLOps practices for reliable model deployment and monitoring.
• Display experience working in hybrid global teams using modern collaboration tools with the ability to manage priorities across multiple parallel AI initiatives.
• Combine strong analytical thinking and problem solving abilities with clear communication skills that make complex AI concepts accessible to diverse stakeholders.
• Apply understanding of responsible AI principles including bias detection explainability privacy preservation and human oversight in all AI design decisions.
• Maintain awareness of current research and industry trends in Agentic AI NLP LLMs and generative AI and translate relevant advances into practical enterprise solutions.

Benefits

• check_circle Medical, Dental & Vision Insurance
• check_circle 401(k) with Company Match
• check_circle Employee Stock Purchase Program
• check_circle Paid Time Off & Holidays
• check_circle Paid Parental Leave
• check_circle Short-Term & Long-Term Disability Coverage
• check_circle Employee Assistance Program (EAP)
• check_circle Mental Health & Wellbeing Programs
• check_circle Health Advocacy & Virtual Care Services

About the company