Minimum qualifications:

　　11 years of experience in data and analytics.

　　Experience in Python and SQL.

　　Experience with people management, stakeholder management, and technical program management.

　　Preferred qualifications: Master's degree in a quantitative discipline (e.g., Statistics, Computer Science, Math, Engineering).

　　Knowledge and experience with both supervised and unsupervised learning (e.g., time series forecasting, clustering, classification) or Big Data techniques (e.g., Spark, Pig, Hive).

　　Ability to manage ambiguity, prioritizing needs, and delivering results in a dynamic environment. Ability to communicate and translate technical solutions and methodologies to executive leadership.

　　Effective problem solving and process improvement skills.

　　About the job

　　At Google, data drives all of our decision-making. As part of the Finance Business Intelligence team, you will use data to inform business and product decisions across the company. Using your technical skills, business acumen and creativity, you will build tools to automate reporting and generate insight that will allow clients to quickly and accurately see how our key business products and processes are performing. Previous experience managing finance systems projects, with emphasis on providing business intelligence and data driven insight through reporting, will have equipped you well for this role. You'll be involved in projects from inception to delivery, ensuring that your reporting delivers high-quality and relevant data to intelligently grow our business. You will also have extensive knowledge of key financial systems, such as Oracle and Hyperion, and experience working with a range of other business intelligence tools and platforms.

　　In this role, you will work on cutting edge data, ML, and AI solutions.

　　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

　　Establish a Finance Data Science, Machine Learning hub in India by establishing the outlook, strategy, objective key results, and defining clear responsibilities. Work cross-functionally with analysts, engineers, and program managers to develop and deploy AI/ML solutions. Improve machine learning scalability, usability, and performance through modeling techniques. Develop and scale reusable analytic libraries for finance and business use cases. Communicate results to peers and leaders. Advocate processes, standards, and engineering practice. Coach junior members and share knowledge with the broader team.