Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

We are seeking a Senior Data Scientist – GenAI & Agentic Systems to join our advanced analytics team supporting leading Investment, Banking, and Financial Services (BFS) clients. In this role, you will design, develop, and deploy state-of-the-art Generative AI and multi-agent solutions that drive critical business decisions across asset management, wealth management, and contact center operations..

Responsibilities:

• Work on the latest applications of data science to solve business problems
• Work directly with client stakeholders to translate business problems into high level analytics solution designs
• Design, develop, and deploy advanced RAG pipelines utilizing semantic chunking, hybrid search (dense + sparse BM25), and cross-encoder re-ranking models
• Build autonomous multi-agent workflows using ReAct loops, native tool calling, complex state management, and deterministic circuit breakers
• Develop parameter-efficient fine-tuning (PEFT) and alignment solutions (LoRA, QLoRA, RLHF, DPO) for large language models
• Translate highly non-linear enterprise problems into scalable AI architectures and technical prototypes
• Present architectural trade-offs (e.g., RoPE vs. ALiBi, MoE routing, Pre/Post-LN) and system designs to senior client stakeholders
• Lead technical deep-dive workshops on LLM evaluation (RAG Triad, LLM-as-a-Judge) and system safety (guardrails, prompt injection defense)
• Implement and operationalize AI models by writing raw, deterministic code, knowing exactly when to bypass heavy framework abstractions (LangChain, LlamaIndex)
• Perform large-scale data extraction, transformation, and analysis using expert-level SQL and Python.
• Partner with asset management, wealth management, and banking teams to understand complex operational requirements and translate them into AI architecture designs.
• Present architectural trade-offs, model insights, and system designs to senior client stakeholders and lead AI strategy discussions.

Requirements

• 8 - 10 years of professional work experience with at least 5 years in Data Science
• Proficiency in Python and SQL
• 8-12 years of hands-on experience in applied Data Science, Machine Learning, and Artificial Intelligence.
• Strong domain experience in Banking & Financial Services (BFS), specifically Asset and Wealth Management. (Backgrounds in Insurance or Contact Center AI/Analytics are also highly considered).
• Deep theoretical and practical knowledge of NLP foundations, Transformer architectures (Multi-Head Self-Attention, Positional Encodings), and vector space mathematics.
• Proven hands-on experience building and deploying Agentic AI solutions and managing complex agent state across directional graphs.
• Expert-level proficiency in Python and SQL; this is a purely hands-on, Individual Contributor (IC) role requiring heavy daily coding.
• Experience configuring and optimizing Vector Databases (e.g., HNSW, IVFFlat indexing).
• Location: Must be based in the US (Malvern, PA or Dallas, TX preferred.

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.