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AI/ML quantitative senior engineering manager

Company: Wells Fargo
Location: West Des Moines
Posted on: November 14, 2022

Job Description:

About this role: Wells Fargo is seeking a Quantitative Solutions Engineering Senior Manager in its Artificial Intelligence Machine Learning Center of Excellence. This team is part of the AI COE responsible for the ideation and delivery of AI/ ML platform and data engineering solutions centered around consumer, commercial and enterprise functions for the bank. As part of our CoE, we invest in you and your career. In addition to Wells Fargo benefits you may be eligible for, you'll have access to elite training platforms like O'Reilly and DataCamp, where you can learn from industry leading experts, along with many other internal and external subject specific education opportunities. You'll be part of a team where there is room to grow, learn, contribute and participate in work being done on world class distributed computing platforms with the latest AI ML framework, both Open Source and licensed, that ultimately supports our customers and company. The AI ML CoE also gives you the opportunity to share your passion for data science through peer education and contributing to programs designed to make the practice more approachable, including one for experienced professionals moving into data science roles. In this role, you will:

  • Ideate, design and solution large-scale data ingestion, data processing, and data transformation pipelines, from various structured and unstructured data sources, supporting on-prem and cloud deployments.
  • Design and drive execution of reusable, parametrized data engineering frameworks to streamline and simplify data acquisition and transformation pipelines.
  • Drive the data engineering strategy and execution for the AI COE as we migrate from on-prem solutions to the public cloud.
  • Work closely with business partners, data scientists, technology teams and ML engineers to create reliable and scalable data engineering solutions and feature stores for different domains.
  • Bring Industry leading best practices and thought leadership into the data engineering practice of the AI COE
  • Provide thought leadership and recommend areas for improvement, especially regarding the adoption of standard tools and the ability to support both batch and real-time pipelines in a standardized manner.
  • Guide data scientists to adopt data engineering best practices during exploration and model training. Get involved in early phases of projects and provide recommendations on the right data pipeline architecture
  • Provide leadership, performance management and work allocation to individual contributors of the data engineering team and ensure adherence to software engineering best practices including technical design and review, unit testing, monitoring, alerting, checking in code and code review
  • Manage teams of individual contributors in roles of operational processes, controls, development, reporting and growth strategies
  • Drive effectiveness while also synchronizing transformational and opportunity needs with pragmatic operational considerations
  • Identify and recommend opportunities for design thinking, modern technology, and government climate in future planning and governance strategies
  • Utilize advanced mathematics to synthesize and communicate concepts into business opportunities for consideration of key stakeholders
  • Determine appropriate strategy and actions with partners, business leaders and executive steering committees
  • Provide ad hoc support of operational or design efforts and troubleshooting when needed
  • Direct team to accomplish goals, resolve the most complex problems or inquires
  • Collaborate and influence all levels of professionals including more experienced managers
  • Lead team to achieve objectives
  • Interact directly with partners within Risk, Legal and outside counsel
  • Manage allocation of people and financial resources for Quantitative Solutions
  • Develop and guide a culture of talent development to meet business objectives and strategy Required Qualifications, US:
    • 6+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
    • 3+ years of Management experience
    • Master's degree or higher in a quantitative field such as mathematics, statistics, engineering, physics, accounting, finance, economics, or computer science
    • 5+ years of experience in relevant fields like data engineering, data warehousing, data lakes, ETL/ELT covering data solutions, architecture, design and implementation
    • 4+ years advanced programming experience across Python, Spark, SQL
    • 4+ years of experience in big data stack technologies like Hadoop, Hive, Kafka
    • 4+ years of experience across SQL databases like Teradata, Oracle and NoSQL databases like MongoDB, Cassandra. Desired Qualifications:
      • Exposure and good understanding of building batch and real-time data pipelines using tool stack in the public cloud (GCP, AWS, Azure)
      • Exposure and good understanding of workflow orchestration technology like Airflow, Kubeflow
      • Hands on experience in migrating data and analytical workloads
      • Experience building streaming data pipelines using Kafka, Apache Beam
      • Knowledge of Google Cloud Storage, BigQuery, Google Dataflow, Cloud Composer, Vertex AI
      • Exposure to the complete AI/ML lifecycle including model development, deployment and model monitoring
      • Familiarity with AI/ML modeling frameworks like Scikit-learn, SparkML, TensorFlow, PyTorch, Keras
      • Familiarity with AI/ML and NLP modeling techniques like Random forest, XGboost, Deep learning, Topic modeling, Text analytics
      • Experience in deployment through containers (like Docker) and orchestration (Kubernetes)
      • Experience with graph databases is a bonus
      • Experience building custom integrations between cloud-based systems using APIs
      • Ability to coach, mentor and build high performing teams
      • Dedicated, enthusiastic, driven and performance-oriented; possesses a strong work ethic and good team player 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.

Keywords: Wells Fargo, West Des Moines , AI/ML quantitative senior engineering manager, Executive , West Des Moines, Iowa

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