Tiger Analytics

Tiger Analytics

Tiger Analytics is a leading advanced analytics consulting firm partnering with Fortune 100 companies to drive business value through expertise in marketing science, customer analytics, and operations analytics.

Professional Services
1K-5K
Founded 2011

Description

  • Work on advanced data science applications to solve business problems.
  • Translate client business problems into high-level analytics solution designs.
  • Present analytical solutions to business audiences and senior management.
  • Develop end-to-end analytics solutions that are efficient, predictable, and sustainable.
  • Design and develop machine learning and Generative AI solutions using RAG.
  • Build LLM-powered applications with Azure OpenAI and orchestrate workflows using LangGraph.
  • Develop agentic AI workflows for automation, insights generation, and decision support.
  • Implement Document Intelligence solutions to extract insights from unstructured data.
  • Participate in technical discussions to select analytic techniques and generate actionable business insights.
  • Develop plans to operationalize analytics solutions and support deployment into business use.

Requirements

  • 6+ years of experience working as a GenAI Data Scientist.
  • 5-10 years of professional work experience, including at least 5 years in Data Science.
  • Proficiency in Python and SQL.
  • Experience with MLflow and model lifecycle management.
  • Experience with Python in a functional programming style, including dependency management, virtual environments, and git version control.
  • Strong understanding of LLMs, prompt engineering, retrieval-augmented generation (RAG), and other generative AI applications.
  • Experience with sequential algorithms such as LSTM, RNN, and transformers.
  • Experience with Bedrock, JumpStart, and HuggingFace.
  • Experience evaluating ethical implications of AI and using red-teaming or similar controls.
  • Expertise in supervised learning, unsupervised learning, deep learning, and transfer learning.
  • Experience with generative algorithms such as GANs and VAEs, as well as pre-trained models such as LLaMa and SAM.
  • Experience developing models from inception through deployment.
  • 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 degree in Business Analytics or equivalent work experience.

Benefits

  • Significant career development opportunities as the company grows.
  • Opportunity to work in a small, fast-growing, challenging, entrepreneurial environment.
  • High degree of individual responsibility.
  • Equal employment opportunities regardless of protected characteristics.

Interested in this position?

Apply directly on the company website

Apply Now

Similar Roles

Lead Insurance Data Scientist - P&C

EPIC Insurance Brokers & Consultants is seeking a Data Scientist to develop and operationalize analytics, dashboards, and data-driven solutions for its commercial Property & Casualty business using the Azure Databricks platform.

Power BI Python SQL Tableau
18 hours, 14 minutes ago

Data Scientist

Imagine Pediatrics 11-50 Health Care Providers & Services

Imagine Pediatrics is seeking a Data Scientist to use healthcare data and machine learning to generate insights that improve care for children with special health care needs.

AWS Machine Learning Python Snowflake SQL Tableau
18 hours, 29 minutes ago

Data Scientist

Imagine Pediatrics 11-50 Health Care Providers & Services

Imagine Pediatrics is hiring a Data Scientist to use foundational data science and machine learning to improve care and outcomes for children with special healthcare needs across its virtual-first and in-home care model.

AWS Dagster dbt Machine Learning Python Snowflake SQL Statistics Tableau
18 hours, 29 minutes ago

Sr Data Scientist Lead

Coderio 51-250 Internet Software & Services

Coderio is seeking a Senior Data Scientist Lead to guide international client initiatives across the full data science lifecycle, from business problem definition through production deployment and optimization, while delivering measurable business value.

Apache Spark AWS Docker Feature Engineering Generative AI Kubernetes Machine Learning MLOps NumPy Pandas Python Scikit-learn SQL
18 hours, 59 minutes ago

You're on a roll! Sign up now to keep applying.

Sign Up

Already have an account? Log in

Used by 14,729+ remote workers