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Job Description & How to Apply Below
Data Scientist – AI & Advanced Analytics
About the role
We are seeking a visionary Data Scientist to spearhead our AI and advanced analytics initiatives with the agency & customer domain. This role is ideal for a seasoned professional who thrives at the intersection of cutting-edge technology, ethical AI, and strategic business impact. You will lead the development and deployment of high0impact data science solutions, drive innovation in the development and deployment of high-impact data science solutions, drive innovation in Generative and Agentic AI, and champion responsible AI practices across the organization.
Key Responsibilities:
• Model Development & Deployment:
Build, test, deliver, and maintain robust data science and AI models that solve complex business challenges.
• Responsible AI Leadership:
Embed the highest standards of AI ethics and responsible AI in all phases of model development and deployment.
• Business Alignment:
Influence and translate strategic business objectives into actionable data science requirements.
• Health Pillar Support:
Drive ideation and delivery of advanced analytics and AI solutions within the health vertical especially on AI based conversational chatbots.
• Conversational AI Ownership:
Lead the design, development, and optimization of intelligent chatbots and conversational agents.
• Innovation & Thought Leadership:
Continuously explore and implement solutions in Generative and Agentic AI.
• Team Leadership:
Mentor and work manage a high-performing team of data and AI engineers, fostering a culture of collaboration and excellence.
Qualifications & Skills
Qualifications Details
Education Bachelor’s or Master’s in Data Science, Computer Science, AI, or related quantitative field
Experience 5+ years (Bachelors) or 3+ years post-Masters in AI/Data Science Programming Expert in Python, SQL, Lang Chain, Hugging Face
Use-Case Experience
Preferably with conversational chatbots utilizing LLMs for intent detection, Geolocation Analytics, Churn Modelling, Cluster Analysis, Recommendation Engine
Cloud Platforms Hands-on experience with Azure or Google Cloud MLOps/AIOps Experience in managing ML artifacts and LLM cost optimization is a strong plus
Leadership Proven track record managing delivery teams of data scientists and AI engineers
Communication Exceptional ability to communicate across technical and non technical audiences
Collaboration Strong team player with cross-functional and cross-geography collaboration skills
Problem Solving Demonstrated critical thinking and analytical capabilities
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