Data Scientist Manager

Data Scientist Manager (Agentic AI & ML Production)Role OverviewWe are looking for a hands-on Data Scientist Manager to lead the development and production deployment of Agentic AI and multi-agent systems for real-world financial services use cases.This role combines team leadership with deep expertise in designing, orchestrating, and operating AI agents in production environments.You will drive the end-to-end lifecycle of AI systems from experimentation to scalable deployment while shaping our agentic AI architecture, standards, and roadmap.Key ResponsibilitiesTeam Leadership & DeliveryLead and coach a team of data scientists to build and deploy production-grade AI/ML and Agentic AI systemsSet technical direction and best practices for building scalable AI solutions aligned with business goalsEnsure strong execution across experimentation, deployment, monitoring, and iterationHire, mentor, and grow talent to build a high-performing AI teamAgentic AI & Multi-Agent SystemsDesign and deploy multi-agent architectures in productionDefine and implement:Orchestrator agents and task routing strategiesTool-calling frameworks and agent-tool integrationAgent-to-Agent (A2A) communication patternsMCP or equivalent tool-integration protocolsArchitect systems that combine:LLM reasoningdeterministic workflowsexternal tools & APIsstructured data sourcesEstablish standards for:agent memory (short-term, long-term, vector memory)context management and retrieval strategiesguardrails and reliabilityevaluation and observabilityProduction & MLOpsOversee deployment of AI/ML and agentic systems into productionEstablish best practices for:model lifecycle managementprompt & agent versioningevaluation frameworksmonitoring and alertingretraining & improvement loopsDefine metrics for agent performance, including:task success ratereasoning qualitylatencycost efficiencybusiness impactCross-Functional CollaborationPartner with Product, Engineering, Risk, and Business teams to identify high-impact use casesTranslate business problems into agentic AI solutionsAct as a thought partner in shaping AI strategy and roadmapSupport regulatory and governance alignment for AI in financial servicesStrategy & InnovationDrive adoption of modern AI frameworks and infrastructureEvaluate tools, vendors, and architectures for agentic systemsStay current with industry trends in:Agentic AILLM orchestrationAI governancefinancial AI regulationQualificationsExperience10+ years in Data Science / AI / ML2+ years leading or managing a teamProven experience deploying AI systems to productionHands-on experience building agentic AI or LLM-based systems in productionTechnical ExpertiseStrong understanding of:Multi-agent architecturesOrchestrator agent designTool calling frameworksMCP or equivalent tool integration conceptsAgent-to-Agent (A2A) communicationMemory systems for agentsEvaluation & monitoring of AI agentsExperience with:LangGraph, LangChain, LlamaIndex or similar frameworksPython, SQLCloud platforms (AWS, GCP, etc.)MLOps / LLMOps toolsVector databases and retrieval systemsNice to have:Reinforcement learningGraph-based reasoningFinancial domain experience (lending, insurance, investment, virtual banking)Leadership & CommunicationStrong ability to lead technical teamsAbility to translate complex AI concepts to business stakeholdersExperience driving AI roadmap and executionWhat We’re Looking ForWe’re looking for someone who:Has actually shipped agentic AI to productionUnderstands system components, not just modelsCan lead a team while staying hands-onThinks in architecture, not just notebooksCan balance innovation with reliability