Data Analytics and Systems Analyst, Tax Technology

Google•Chicago, IL

14h•$116,000 - $166,000

About The Position

At Google, data drives decision-making. This role works on technical challenges across multiple tax areas, supporting the Tax Technology team as it advances data science and Machine Learning Engineering capabilities. The analyst collaborates to create end-to-end data solutions that help tax partners make informed decisions and manage risks and opportunities. The role involves working with data scientists, data engineers, and program managers to implement and deploy machine learning pipelines; creating automation with scripting languages and API integrations; building full-stack technology solutions and internal APIs; and improving machine learning scalability, usability, and performance. Individual pay is determined by job-related skills, experience, and relevant education or training. The stated U.S. compensation is $116,000–$166,000, plus a 15% bonus target, equity, and benefits.

Requirements

Bachelor's degree in Data Science, Computer Science, Information Systems, Finance, Tax, a related quantitative field, or equivalent practical experience.
4 years of experience working with data, including data science methodologies or machine learning applications.
Experience developing or applying machine learning solutions, such as Generative AI, Natural Language Processing (NLP), or Large Language Models (LLMs).
Experience coding in Python and SQL.

Nice To Haves

Master's degree in Data Science, Computer Science, Information Systems, Statistics, or a related quantitative field.
Experience building and deploying end-to-end machine learning models or predictive analytics in production, such as with TensorFlow or Scikit-Learn.
Experience in the design, implementation, and delivery of scalable build/test/release software development lifecycles (SDLC).
Ability to work with cross-functional teams to drive the development and deployment of GenAI and LLM solutions.
Effective written and verbal communication skills to translate technical solutions and methodologies to senior leadership.

Responsibilities

Work cross-functionally with data scientists, data engineers, and program managers to understand, implement, and deploy machine learning pipelines.
Develop and implement automation solutions using scripting languages such as Python to streamline processes and enhance efficiency, involving extensive API integration and management.
Lead the development and deployment of full-stack technology solutions, including web applications (such as Java backend, TypeScript frontend, and gRPC) and internal APIs, ensuring seamless data flow and system interaction.
Improve machine learning scalability, usability, and performance.
Explore technologies and apply them to deliver business benefits.