The Development Group Manager under Financial Planning & Analysis (FP&A) group within Treasury, Tax and Forecasting Technology (TTF) is a senior management position responsible for building out strategic architecture for FP&A business inclusive of AI/ML Capabilities. We are seeking a highly skilled and experienced Senior Manager with real experience in Finance domain to lead the AI/ML initiatives within our Financial Planning & Analysis (FP&A) organization. This role is pivotal in building and expanding our strategic architecture with a focus on integrating AI/ML capabilities to enhance FP&A operations. The Group Manager will oversee the development and deployment of advanced AI/ML solutions, including a sophisticated analytical chatbot leveraging large language models (LLMs) to query both structured and unstructured data, and the implementation of anomaly detection systems in the finance domain.
- Additional Responsibilities
- Strategic Architecture Development: Lead the design and implementation of the AI/ML architecture to support FP&A business functions, focusing on scalability, efficiency, and robustness.
- Data Pipeline & Engineering: Build and optimize data pipelines to support AI/ML initiatives. Collaborate with engineering teams to develop end-to-end solutions that integrate data ingestion, processing, and model deployment.
- Team Leadership:Assemble and manage a cross-functional team, including data scientists, engineers, and UI/UX professionals, to execute AI/ML projects from concept to production.
- Chatbot Development: Oversee the expansion and enhancement of our chatbot capabilities, utilizing LLMs for querying structured and unstructured data. Ensure the chatbot can perform advanced analytical tasks such as variance analysis and earnings report analysis.
- Anomaly Detection:Develop and implement AI-driven anomaly detection systems to monitor and identify irregularities in both structured financial data and unstructured information sources.
- Infrastructure Management:Manage the deployment of AI/ML solutions, including setting up internal GPUs, leveraging internal frameworks like R2D2 and Stellar, and ensuring the infrastructure is optimized for performance and cost-efficiency.
- Technology Expertise:Utilize cutting-edge technologies such as H2O, open-source LLMs, Document Processing Tools, RAG pipeline, Vector Databases such as ChromDB, PostresSQL and other Python libraries to build robust AI/ML models.
- Collaboration & Communication:Work closely with stakeholders across the organization to understand business needs and translate them into AI/ML solutions. Communicate complex technical concepts to non-technical audiences effectively.
- Additional Qualifications
- 10+ years of experience in Finance projects, with a strong focus on strategic architecture and AI/ML solutions deployment in the finance domain.
- Must have hands on experience with LLM (commercial and open source) such as Mixtral/Llama3/Gemini, LangChain, Llama Index, RAG pipeline, Embedding Models, Re-Ranker Models and Vector Databases such as ChromDB, PostgreSQL
- Must have experience in leading AI/ML Finance projects, particularly in developing chatbots for querying Finance both structured/unstructured and implementing anomaly detection use cases.
- Must have experience with setting up internal GPUs, R2D2, Stellar, H2O and other proprietary frameworks.
- Strong leadership and team management skills, with the ability to mentor and guide technical teams.
- Proficiency in Python, machine learning frameworks (e.g., TensorFlow, PyTorch), and data engineering tools.
- Excellent communication and collaboration skills, with the ability to work effectively across business and technical teams.
Bachelor’s degree with real-world experience.
Will also consider previous projects or practical work done in the AI/ML space specially in Finance industry.
PMP Certification is a plus
Certifications in AI/ML space is a plus
Applications DevelopmentFull timeTampa Florida United States$141,440.00 - $212,160.00
Anticipated Posting Close Date:
Sep 26, 2024View the " " poster. View the .
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