Wells Fargo Senior Quantitative Analytics Specialist 

India, Karnataka, Bengaluru 

724051575

In this role, you will:

• Design, develop, and deliver large-scale data ingestion, data processing, and data transformation projects, 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 the most suitable and scaled data engineering solutions, feature stores, etc.
• Automate data ingestion, pipelines and feature creation processes across tabular, semi-structured, free text, voice and image data. Figure out efficient ways to transform and store for scaled modeling usage
• As a senior member of the Data engineering team, contribute to development and scaling of end-to-end Data engineering team and capability. Guide junior engineers to build best-in class frameworks. Work with data science, ML engineers and technology partners and chalk out the roadmap and implementation strategy
• Guide data scientists to adopt data ingestion best practices during model exploration, development and deployment. Get involved in early scoping phases of projects/products and provide thought leadership on the right pipeline architecture
• Contribute to cloud migration strategy for data engineering and ML Ops solutions. Migrate data infrastructure from on-prem to private and public cloud (GCP)
• Keep up with emerging best practices in data engineering and drive adoption as necessary.
• Advocates for and ensures their team adheres to software engineering best practices (e.g. technical design and review, unit testing, monitoring, alerting, checking in code, code review)

Required Qualifications:

• B.S/B.Tech/B.E. degree or higher in a quantitative field such as computer sciences, applied math, statistics, engineering
• 6-10 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 in Python, Spark, SQL, Scala, SAS (expert level proficiency)
• 4+ years of experience in big data stack like Hadoop, Hive, Kafka, Impala (expert level proficiency)
• 4+ years of experience across SQL databases like Teradata, Oracle and NoSQL databases like MongoDB, Cassandra. Experience of graph databases is a bonus
• 2+ years of experience in ML workflow technology like Airflow, Kubeflow
• Experience with implementing CI/CD principles and version control in the Machine Learning domain
• Exposure to tools like Databricks/Dataiku
• Experience creating data pipelines and ML Ops environment on Cloud (GCP, AWS, Azure) (GCP - preferred). Hands on experience on migrating data infrastructure from on-prem to GCP will be a bonus.BigQuery, Cloud Composer, Vertex AI
• Ability to interact with both business and technology partners on tech migration/adoption
• Takes ownership for responsibilities for own and drive same effort to the team
• Dedicated, enthusiastic, driven andperformance-oriented;possesses a strong work ethic and good team player

Desired Qualifications:

• Experience in Agile development methods
• 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 banking and BFSI, retail, e-commerce, product companies (preferred)
• Experience in deployment through containers (like Docker) and orchestration (Kubernetes)
• Experience in deploying Machine Learning as-a-service using REST API’s, Flask, Django, etc.
• Experience building custom integrations between cloud-based systems using APIs
• Experience with elastic search, knowledge graph
• Experience with ML model testing: model performance, model health, etc.

Job Expectations:

• As mentioned above

26 Feb 2025

Wells Fargo Recruitment and Hiring Requirements:

b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.