Tiger Analytics
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, and 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 Forrester and Gartner.
As a Data Scientist, you will apply strong expertise in AI through machine learning, data mining, and information retrieval to design, prototype, and build next‑generation advanced analytics engines and services. You will collaborate with cross‑functional teams and business partners to define the technical problem statement and hypotheses, develop efficient and accurate analytical models, and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills and ensuring business value while communicating the results.
Key Responsibilities
Implement efficient Retrieval‑Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure
Collaborate with cross‑functional teams to integrate solutions into operational processes and systems supporting various functions
Stay up to date with industry advancements in AI and apply modern technologies and methodologies to our systems
Design, build and maintain scalable and robust real‑time data streaming pipelines using technologies such as GCP, Vertex AI, S3, AWS Bedrock, Spark streaming, or similar
Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics, etc.
Ensure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management
Implement best practices in reliability engineering, including redundancy, fault tolerance, and disaster recovery strategies
Collaborate closely with DevOps and infrastructure teams to ensure seamless deployment, operation, and of data systems
Mentor junior team members and engage in communities of practice to deliver high‑quality data and AI solutions while promoting best practices, standards, and adoption of reusable patterns
Apply AI solutions to insurance‑specific data use cases and challenges
Partner with architects and stakeholders to influence and implement the vision the AI and data pipelines while safeguarding the integrity and scalability of the environment
Requirements
7 years of experience working as a GenAI Data Scientist
Experience with Python from a functional programming paradigm, managing dependencies and virtual environments, and version control in Git
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‑team testing)
Expertise in supervised and unsupervised learning, 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
Benefits 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.
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As a Data Scientist, you will apply strong expertise in AI through machine learning, data mining, and information retrieval to design, prototype, and build next‑generation advanced analytics engines and services. You will collaborate with cross‑functional teams and business partners to define the technical problem statement and hypotheses, develop efficient and accurate analytical models, and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills and ensuring business value while communicating the results.
Key Responsibilities
Implement efficient Retrieval‑Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure
Collaborate with cross‑functional teams to integrate solutions into operational processes and systems supporting various functions
Stay up to date with industry advancements in AI and apply modern technologies and methodologies to our systems
Design, build and maintain scalable and robust real‑time data streaming pipelines using technologies such as GCP, Vertex AI, S3, AWS Bedrock, Spark streaming, or similar
Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics, etc.
Ensure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management
Implement best practices in reliability engineering, including redundancy, fault tolerance, and disaster recovery strategies
Collaborate closely with DevOps and infrastructure teams to ensure seamless deployment, operation, and of data systems
Mentor junior team members and engage in communities of practice to deliver high‑quality data and AI solutions while promoting best practices, standards, and adoption of reusable patterns
Apply AI solutions to insurance‑specific data use cases and challenges
Partner with architects and stakeholders to influence and implement the vision the AI and data pipelines while safeguarding the integrity and scalability of the environment
Requirements
7 years of experience working as a GenAI Data Scientist
Experience with Python from a functional programming paradigm, managing dependencies and virtual environments, and version control in Git
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‑team testing)
Expertise in supervised and unsupervised learning, 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
Benefits 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.
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