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Business Data Scientist, Finance

Business Data Scientist, Finance

1 Month ago • 5 Years + • Data Analyst

About the job

8 skills required for this role

Test your skills to join the top 1% applicants for this job

prototyping

data-visualization

python

sql

data-science

tableau

communication

innovation

Job Description

The Business Data Scientist, Finance at Google's Finance Data and Analytics (DnA) team will analyze large datasets, build expert systems, and improve product performance. Responsibilities include complex statistical analysis, model embedding in production systems, managing changing business priorities, and interfacing with product managers and engineers. The role involves partnering with finance leadership, working with ML Scientists and Engineers to improve model usability, developing and improving models, providing insightful analyses using advanced analytics, and creating reusable analytic frameworks. Collaboration with Data Scientists, Data Engineers, and Project Managers is key to creating data products that enable informed financial decisions and risk management across various business areas (Ads, YouTube, Search, Play, etc.).

Must have:

Bachelor's degree in quantitative discipline
5 years data analyst/scientist experience
Statistical analysis & predictive analytics skills
Experience with Python, SQL, and data visualization tools
Excellent communication skills
Partner with finance leadership to deliver insights

Good to have:

Time series data analysis experience
Stakeholder/client-facing experience
Experience improving ML model usability

Minimum qualifications:

Bachelor's degree Statistics, Economics, Mathematics, in a quantitative discipline, or equivalent practical experience.
5 years of experience in the Industry in a Data Analyst or Data Science role, analyzing data sets to solve business problems through statistical methods and predictive analytics.

Preferred qualifications:

Experience in data analysis, especially for time series data, to solve business problems in complex, fast-moving, and ambiguous business environments with strong data intuition and business acumen.
Experience in stakeholder-facing or client-facing roles (e.g. previous consulting role).
Experience with statistical softwares (e.g., Python), database languages (e.g., SQL), and data visualization tools (e.g., Tableau).
Excellent communication skills (written and verbal) to translate technical solutions and methodologies to leadership.

About the job

As a Quantitative Analyst, you will be responsible for analyzing large data sets and building expert systems that improve our understanding of the Web and improve the performance of our products. This effort includes performing complex statistical analysis on non-routine problems and working with engineers to embed models into production systems. You will manage fast changing business priorities and interface with product managers and engineers.

The Finance Data and Analytics (DnA) team combines business acumen, technology and innovation to organize data, enable insights and create data driven and efficient Finance organization in Google. At Google, data drives all of our decision-making. You will be part of a growing Data Science team for Data Scientists and Machine Learning Engineers. You will work on strategic business challenges across multiple business areas (e.g., Ads, YouTube, Search, Play, etc.) through the lens of business generation. You will collaborate with Data Scientists, Data Engineers, and Project Managers to create data products to enable our finance partners to make informed decisions, manage risks and opportunities.

Responsibilities

Partner with Finance leadership and their teams to understand business context, ideate, and deliver insights and prototypes.
Work with Machine Learning Scientists and Engineers to improve usability of the Machine Learning models through the design of appropriate metrics.
Collaborate with Machine Learning Scientists to develop and improve models (e.g., identifying new data sources, hypothesis testing, feature engineering, model prototyping, analyzing model output and model explainability).
Provide analyses through advanced analytics/statistical methods that tell a story focused on business insights.
Develop reusable and robust analytic frameworks to ensure consistent results across business areas. Contribute to a culture of learning, sharing and making Machine Learning accessible across the broader team and our stakeholders.

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About The Company

Google

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A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.