About this role:
About this role:
Wells Fargo is seeking a Senior Lead Quantitative Solutions Engineering Specialist.
This team is responsible for the ideation and delivery of AI and 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. Our diverse data science team ranges from university professors and experienced practitioners to data scientists new to the industry, creating a full spectrum of thought leadership and solution design. 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:
- Design, develop, and deliver large-scale data ingestion, data processing, and data transformation pipelines, from various structured and unstructured data sources, supporting on-prem and cloud deployments.
- Work closely with business partners, data scientists, technology teams and ML engineers to create reliable and scalable data engineering solutions and feature stores.
- Actively contribute to our cloud journey, as we migrate from on-prem solutions to a hybrid approach that will also leverage capabilities from GCP.
- Provide thought leadership and recommend areas for improvement, especially in regard to 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 pipeline architecture
- Provide leadership to more junior members 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
- Advise more experienced leadership in developing objectives, plans, and resources for highly complex business and engineering needs
- Perform complex activities on visual dashboards on a routine basis with detailed reporting to show improvement
- Collaborate with business unit manufacturing sites to focus on new engineering solutions focusing on new and existing product quality
- Lead the strategy and resolution of highly complex and unique challenges during real time decisions
- Mediate between computer software and hardware in their design and production phase
- Deliver engineering solutions that are large-scale and require vision, creativity, innovation, and inductive thinking
- Provide vision, direction, and expertise to more experienced leadership on implementing innovative and significant business solutions
- Collaborate and consult with peers, colleagues, and managers to resolve issues and achieve goals
Required Qualifications, US:
- 7+ years of Quantitative Solutions Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- 6+ 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.
- 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
- Dedicated, enthusiastic, driven and performance-oriented; possesses a strong work ethic and good team player
- Hands on experience in migrating data and analytical workloads
- B.S/B.Tech/B.E. degree or higher in a quantitative field
- Experience building streaming data pipelines using Kafka, Apache Beam
- Knowledge of Google Cloud Storage, BigQuery, 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
- Addison, TX
- Charlotte, NC
- Fort Mill, SC
- Minneapolis, MN
- Tempe, AZ
- San Francisco, CA
- West Des Moines, IA
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.