Data Scientist, Extended Workforce Solutions

Minimum qualifications:

• Master's degree in a STEM field or equivalent practical experience.
  
• 4 years of industry or PhD Data Science experience.
• Experience in causal inference, A/B testing, statistical modeling, or Machine Learning (ML).
• Experience with programming in SQL and Python, leveraging ML or statistical libraries (e.g. TensorFlow, Scikit-learn, XGBoost, Keras, Pandas).

Preferred qualifications:

• PhD in a STEM field.
  
• Publications related to Data Science, posters or presentations in Artificial Intelligence/Machine Learning (AI/ML) conferences, or patents.
• Experience in a Data Science role supporting Sales, Marketing, or Customer Support.
• Experience in Natural Language Processing (NLP), Large Language Models (LLMs), Generative Artificial Intelligence (AI), and R.
• Experience drawing conclusions from data, breaking down technical concepts into simple terms, connecting with, and presenting to, technical and non-technical stakeholders, and recommending actions.

About the job

gTech's Extended Workforce Solutions (xWS) team enables Product Areas (PA) to effectively and efficiently scale their outsourced operations while managing risk. In this role, you will enable Google's businesses to make informed decisions to put the right talent in the right locations. You will partner with teams across Google to provide an excellent user experience and minimize administrative burden throughout the Extended Workforce process. You will assist with Extended Workforce planning and strategy, and provide tools to support PAs in managing their xWS infrastructure. You will balance between optimizing outsourcing engagements and making sure xWS policies and guidelines are followed for growth and success.

Responsibilities

• Translate Extended Workforce Solutions(xWS) data strategy and leverage expertise to deliver solutions for users.Develop the data infrastructure, project planning, and solution roadmap development.
• Collaborate with Leadership, Engineering, and PA teams to establish performance objectives, key performance indicators (KPI), and other success metrics for xWS projects and processes.
• Work with large, complex internal data sets; solve difficult, non-routine analysis problems, applying advanced investigative methods as needed. Act as thought partner to produce insights and metrics for various technical and business stakeholders.
• Collaborate with technical stakeholders to provide insights and recommendations driven by data analysis and business objectives. Execute comprehensive data analysis projects, encompassing data collection, requirements definition, processing, analysis, and ongoing reporting through presentations and deliverables.
• Deliver effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.