Job Description
When you join Verizon
Verizon is one of the world’s leading providers of technology and communications services, transforming the way we connect across the globe. We’re a diverse network of people driven by our shared ambition to shape a better future. Here, we have the ability to learn and grow at the speed of technology, and the space to create within every role. Together, we are moving the world forward – and you can too. Dream it. Build it. Do it here.
What you’ll be doing...
As a Fraud Data scientist, you will be working with a passionate group of professionals who apply cutting edge AI/ML technology to protect Verizon customer accounts from account takeovers, illegal SIM Swaps, Port Outs etc as well as prevent financial losses resulting from fraudulent activity.
- Lead projects focused on reducing Fraud loss and customer friction involving hands-on data analysis, Machine Learning modeling and other standard data science techniques.
- Translate real world problems into solvable Machine Learning problems leading to actionable insights.
- Respond rapidly to emerging threats, both internal and external, with proactive monitoring and swift deployment of new controls.
- Engage with business partners and collaborate with cross functional teams to define and evaluate business problems, design and implement effective, innovative analytical solutions and models with the right choice of technology and level of complexity for the business challenges.
- Identifies, analyzes, and interprets trends or patterns in large complex data sets. Translate data into insights and utilize that to implement solutions for business problems.
- Apply link analysis to identify hidden connections in the data to proactively detect nascent fraud rings.
- Lead the design and development of ML based anomaly detection and chart overlays.
- Responsible for developing strategies for effective reporting, use graphs, infographics and other tools to visualize data
- Monitor analytics & metrics results and take action.
- Building tools and frameworks to automate data collection.
- Helps define the analytical roadmap, data and technology strategy. Conduct market analysis, research to identify and adopt best in class data science and analytics related technology.
Where you'll be working...
This hybrid role will have a defined work location that includes work from home and assigned office days as set by the manager.
What we’re looking for...
You’ll need to have
- Bachelor’s degree or four or more years of work experience
- Six or more years of relevant work experience
- Experience as a data scientist and preferably worked on a wide array of domains.
- Experience with modeling techniques like Linear Regression, Logistic Regression (Binomial and Multi-Class), Robust Regression, DBSCAN, Text Analytics (NLP), 3 Dimensional Tensor Factorization, Time-Series Analysis, Clustering, Holt-Winter’s Forecasting Technique, Decision Tree Analysis, Boosted Decision Tree Analysis, CNN’s like Resnet, Inception etc.
- Willingness to travel
Even better if you have
- Master’s degree in Math / Statistics / Computer Science or related discipline.
- Knowledge in Background in Predictive Analytics, Machine Learning, Consulting Reporting, and Business Development
- Experience in Risk management/modeling experience.
- Experience with AWS experience is a plus.
- Knowledge in the background in Statistics.
- Experience in business intelligence tools like Qlik, ELK
- Experience with Python (including packages like SciKitLearn, NumPy, pandas)
- Experience with SQL proficiency one or many (Postgres, Oracle, SQL Server, Teradata)
- Knowledge Graph DB knowledge
- Knowledge Programming Language(s): Experience in combinations of SAS, SQL, R, Python, Java
- Knowledge OS/HW: Experience in Linux/Unix open systems, AWS environment
- Excellent communication skills to present complex ideas and concepts to technical and non-technical audiences.
- Solid experience in writing SQL, stored procedures, query performance tuning preferably on Oracle, PostgreSQL
Company Info.
Verizon
Verizon is an American wireless network operator that previously operated as a separate division of Verizon Communications under the name of Verizon Wireless.
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