Tiger Analytics

Delivers Data and AI transformation

Lead Data Scientist - GenAI

Natural Language Processing & LLMsConfirmed live in the last 24 hours

Full-timeRemote in USANo salary listedRemote

About the Job

Requirements

At least 6 years of experience working as a GenAI data scientist, with 5–10 years of professional work experience and at least 5 years in data science.
Proficiency in Python and SQL.
Experience with MLflow and model lifecycle management.
Experience using Python within a functional programming paradigm, managing dependencies and virtual environments, and using Git for version control.
Solid understanding of generative AI concepts, including large language models, prompt engineering, retrieval-augmented generation, and contemporary generative AI applications.
Experience with sequential algorithms such as LSTM, RNN, and transformers.
Experience with Amazon Bedrock, JumpStart, and Hugging Face.
Experience evaluating ethical implications of AI and mitigating them, including red-teaming.
Expertise in supervised and unsupervised learning, deep learning, and transfer learning.
Experience with generative algorithms such as GANs and VAEs, as well as pretrained models such as LLaMA and SAM.
Experience developing models from inception through deployment.
Experience building end-to-end machine-learning pipelines in production.
Familiarity with CI/CD pipelines, monitoring, and model governance.
Ability to design scalable and reliable AI systems.
Bachelor's degree in Business Analytics or equivalent work experience.

Responsibilities

Apply data science to solve business problems.
Work directly with client stakeholders to translate business problems into high-level analytics solution designs.
Present analytic solutions to business audiences, highlighting solution robustness and potential business value.
Develop end-to-end solutions based on an in-depth understanding of business problems, delivering analytics solutions efficiently, predictably, and sustainably.
Design and develop machine-learning and generative AI solutions using retrieval-augmented generation.
Build large-language-model-powered applications using Azure OpenAI and orchestrate workflows with LangGraph.
Develop agentic AI workflows for automation, insight generation, and decision support.
Implement document-intelligence solutions to extract insights from unstructured data.
Discuss and select relevant analytic techniques with team members to create actionable business insights.
Present results to senior management and business teams, and develop plans to operationalize analytic solutions.

Lead Data Scientist - GenAI

Tiger Analytics Inc. · United States (Remote) · Full-time · Posted 2026-05-15

Workplace: remote

Department: Data Science

Description

Tiger Analytics is looking for experienced Data Scientists GenAI 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 highly skilled and experienced Lead Data Scientist with strong expertise in GenAI modelling. The ideal candidate will have a proven track record of designing, developing, and deploying scalable GenAI solutions, while leading projects and mentoring teams. This role requires deep technical expertise, hands-on coding experience, and the ability to collaborate closely with clients and stakeholders to translate business needs into robust analytical solutions.

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
Present analytic solutions to business audiences highlighting robustness of the solution and how it could help generate business value
Develop end-to-end solutions based on in-depth understanding of business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably
Design and develop machine learning and Generative AI solutions using RAG
Build LLM-powered applications leveraging Azure OpenAI and orchestrate workflows using LangGraph
Develop agentic AI workflows for automation, insights generation, and decision support
Implement Document Intelligence solutions for extracting insights from unstructured data
Participate in discussions with team members to select and apply relevant analytic techniques and create actionable business insights
Responsible for making presentations to senior management, communicating results to business teams, and develop plans to help operationalize analytic solution

Requirements

6+ years of experience working as a GenAI Data Science.
Proficiency in Python and SQL
Experience with MLflow and model lifecycle management
Experience with Python from a functional programming paradigm, able to manage dependencies and virtual environments, along with version control in git
Generative AI Knowledge: Solid understanding of latest-generation AI concepts including LLMs, prompt engineering, retrieval-augmented generation (RAG), and other contemporary generative AI applications
Experience with sequential algorithms (e.g., LSTM, RNN, transformer, etc.)
Experience with Bedrock, JumpStart, HuggingFace
Experience evaluating ethical implications of AI and controlling for them (e.g., red-teaming)
Expertise in supervised learning and unsupervised learning along with experience in deep learning and transfer learning
Experience in generative algorithms (e.g., GAN, VAE, etc.) as well as pre-trained models (e.g., LLaMa, SAM, etc.)
Experience developing models from inception to deployment 5-10 years of professional work experience with at least 5 years in Data Science.
Experience building end-to-end ML pipelines in production
Familiarity with CI/CD pipelines, monitoring, and model governance
Ability to design scalable and reliable AI systems
Bachelor's in Business Analytics or equivalent work experience.

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.

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.

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About the Company

Tiger Analytics

Delivers Data and AI transformation

Tiger Analytics helps large organizations plan and execute Data and AI–led transformations at scale. It works with clients to translate business needs into data and AI initiatives, using an approach that combines business value mapping, agile operating models, and a platforms-based architecture, backed by partnerships with major hyperscalers. The company designs and delivers end-to-end data and AI solutions—from strategy and data engineering to model development and deployment—so that AI can be applied to tough, real-world problems. Unlike firms that rely mainly on standard playbooks, Tiger Analytics builds custom approaches and accelerators to suit each client’s value chain and operating model. With a global team of 5000+ technologists and consultants, the goal is to enable measurable value and practical outcomes through data and AI programs that work at enterprise scale.

Company size: 1,001-5,000
Company stage: Not listed
Total funding: Not listed
Headquarters: San Jose, CA
Founded: 2010

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