Product Analytics Manager

About the company

We're working with the market-leading cloud solution for authenticating digital personas and transactions on the Internet. These guys are verifying more than 20 billion annual transactions supporting 30,000 websites and 4,500 customers globally. Their flagship solution is deployed across a variety of industries, including financial services, e-commerce, payments and lending, media, government and insurance.

Description

• Use data from the largest real-time fraud detection platform on the planet to craft solutions with data analysis, statistical modeling, and supervised machine learning. This role has the potential to cause the most immediate real-world impact in the form of increased profits, lower authentication friction, and reduced credential abuse.You’ll leverage a real-time platform analyzing billions of transactions per month for our Fortune 500 customers in Financial Services, Insurance, e-Commerce, and On-Demand Services. These tools will allow you to attain a unique perspective of the Internet and every persona connected to it.

• You’ll be continually collaborating with internal services and engineering teams, customer-facing account teams, and external business leaders and risk managers. The data driven prototypes, reports and models you build will go head-to-head against some of the most motivated attackers in the world to protect billions in revenue.

Responsibilities

• Direct and execute multiple medium to large analytic projects along with rest of the stakeholders in the services, engineering & products team

• Build prototypes to demonstrate innovative data driven product ideas

• Assist in monitoring and maintaining global fraud detection policies, models & reports

• Collaborate with the internal teams to fully understand business requirements and desired business outcomes

• Contribute to the development of the team's analytical skills and business knowledge

• Be the face of data in the organization and promote

Data/Technical qualifications

• 3+ years of analytical experience and graduate degree in Quantitative field such as Statistics, Mathematics, Computer Science, Economics, or equivalent experience preferred

• Demonstrated hands on expertise with Hadoop (Imapala/Hive)/SQL & Python

• Proficiency in some of the following statistical techniques: Linear & Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Neural Networks, Clustering, Principal Component Analysis, Factor analysis, etc

• Demonstrated experience in planning, organizing, and managing multiple analytic projects with diverse cross-functional stakeholders

All your information will be kept confidential according to EEO guidelines.