About this role:
Wells Fargo is seeking a Senior Fraud Mgmt. Data Scientist. In this role, you will be building advanced models with the goal of reducing fraud losses, reducing false positives in existing A.I. based fraud detection capabilities, and helping improve the overall customer experience.
In this role, you will:
Work with cross functional teams to identify, strategize, and execute Artificial Intelligence initiatives focused around Fraud Mgmt.
You will be working with the team to design, code, train, test, deploy, and iterate on large scale cloud-native machine learning platforms, focused on fraud related usecases
Use Data Science skills to investigate data, develop models and analytics in order to detect and prevent fraud
Use Link Analysis and Graph based analytics to discover account abuse and identify fraudulent activities
Build advanced neural network capabilities to detect and identify fraud
You will be shaping the direction of machine learning and artificial intelligence at Wells Fargo
Decision key issues which may arise during development or implementation
Collaborate and consult with peers, colleagues and managers to resolve and achieve goals
Required Qualifications, US:
4+ years of Artificial Intelligence experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- 2+ years of experience in data science practice using SQL and Python (scikit learn, Pandas, NumPy, etc.), R
- 2+ years of experience in development of machine learning and deep learning models using tools such as H2O or similar advanced analytical tools
- 2+ years of experience in modern data mining and data science techniques (e.g., regressions, decision trees, ensemble algorithms, neural networks, time series analytics, clustering, anomaly detection, text analytics, etc.)
- 2+ years experience using Spark for data investigation, exploratory analysis, and initial analytic development
Knowledge of graph database technologies is a plus
Prior experience using advanced ML techniques and algorithms such as RNN, LSTM, Graph Neural Networks is a plus
Working and utilizing cloud-native A.I. capabilities on Google Cloud (e.g., Big Query for data storage, Vertex A.I., Auto ML, BigTable, GCP Pub/Sub or dataflow for streaming, Tensorflow)
Experience using synthetic datasets for model development
Ability to work additional hours outside regular business hours.
We Value Diversity
At Wells Fargo, we believe in diversity, equity and inclusion in the workplace; accordingly, we welcome applications for employment from all qualified candidates, regardless of race, color, gender, national origin, religion, age, sexual orientation, gender identity, gender expression, genetic information, individuals with disabilities, pregnancy, marital status, status as a protected veteran or any other status protected by applicable law.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.
Candidates applying to job openings posted in US: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
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