Business Data Science Manager, Finance

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

Minimum qualifications:

• Bachelor's degree in a quantitative discipline or equivalent practical experience.
• 10 years of experience in a Data Analyst or quantitative role.
• Experience with statistical software (Python or R), database languages (SQL) and data visualization tools (Tableau, Looker, or Power BI).
• People management experience.

Preferred qualifications:

• Master's degree or higher in a quantitative discipline (e.g., Statistics, Computer Science, Math, Engineering) or equivalent practical experience.
• Data intuition and business acumen, with experience in data analysis to solve business problems in complex, fast-moving, and ambiguous business environments.
• Familiarity with analytics methods/theory (statistics, ML, etc.), data programming libraries (Pandas, Numpy, Scikit-learn etc.) and ability to identify opportunities to apply these.
• Effective communication (written and verbal) to translate technical solutions and methodologies to executive leadership.
• Excellent people leadership, coaching, and teaching skills in emerging practices in statistical analysis and advanced analytics.

About the job

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. As part of this team, you will have a unique opportunity to gain perspectives on Google’s core businesses, services and the products.

At Google, data drives all of our decision-making. As a Business Data Science Manager, you will be part of a growing Data Science team for Analysts, Scientists and Engineers. You will work on strategic business challenges across multiple business areas (e.g. Ads, YouTube, Search, Play, etc.) through the lens of growth. You will build and lead a team and collaborate with Data Scientists, Data Engineers, and Project Managers to create end-to-end data products to enable our finance partners to make informed decisions, manage risks and opportunities.

The name Google came from googol, a mathematical term for the number 1 followed by 100 zeros. And nobody at Google loves big numbers like the Finance team when providing in depth analysis on all manner of strategic decisions across Google products. From developing forward-thinking analysis to generating management reports to scaling our automated financial processes, the Finance organization is an important partner and advisor to the business.

Responsibilities

• Build and lead a team to partner with Finance leadership and their teams and translate strategic and operating plans into meaningful direction of projects, goals, priorities and activities.
• Lead efforts to provide analyses through advanced analytics/statistical methods that tell a “story” focused on business insights, and develop reusable and robust analytic frameworks to ensure consistent results across business areas.
• Ensure the team to leverage visualization to summarize the data insights and effectively employ clear and structured communication to tech and non-tech audiences.
• Build alignment for vision/strategy of using Machine Learning with Data Scientist and support Data Scientists on performing additional exploratory data analysis for feature engineering, and analyzing model outputs, and relationship with features for model performance improvement.
• Oversee the technical quality of your team’s work, and ensure that it adheres to excellence.