Marketing Data Scientist, gTech

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 Computer Science, Mathematics, Statistics, Engineering, a related field, or equivalent practical experience.
• Experience in coding within Python or R and SQL.
• Ability to speak and write in English and Japanese fluently.

Preferred qualifications:

• 6 years of experience working in an analytical field (e.g., management consulting, investment banking, internet/media industries, etc.).
• 6 years of industry experience in a consumer-internet, web analytics, or related role with experience in SQL, Data Visualization, Dashboarding, and Descriptive Statistics.
• Experience in translating business questions into analyses and analysis results into actionable business-relevant recommendations.

About the job

The gPS Marketing Data Science team helps measure and optimize marketing ROI for customers. We help build bespoke models that address customer's key business questions. We learn the innovative technologies that drive Google products and bring those innovations to life in the context of specific customer engagements.

We are positioned within gTech’s Professional Services team which takes a creative, collaborative, and customer-centric approach to provide consulting and solutions to advertisers and agency partners. Through technical implementation, optimization, and engineering solutions, gTech Professional Services helps customers achieve their business goals while building long-term tech and marketing capabilities.

Responsibilities

• Lead analytics aspects of customer engagements in the area of marketing effectiveness and marketing portfolio management.
• Partner with customers to build a machine learning framework. Engage stakeholders, assess data readiness, and be able to scale a proof of concept to a larger solution.
• Partner with customers and internal teams to translate data and model results into tactical/strategic insights that are clear, complete, accurate, relevant, understandable, and applicable to decision making and needs for varying customer audiences.
• Partner with Product/Engineering teams to increase and optimize capabilities, employing methods which create opportunities for scale and proactively help drive innovation.
• Develop a comprehensive understanding of Google data structures and metrics, advocating for product changes where needed.