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Company Name :
Wells Fargo
Location : Bengaluru, Karnataka
Position :

Job Description : About this role:

The Enterprise Analytics and Data Science (EADS) organization is looking for an established and proven ML Ops and Data Engineering expert to join our team and help us build scalable ML platform for the E-AA Lab program. This E-AA Lab/BLADE enables innovation across all LOBs and departments by carrying out advanced machine learning, natural language processing, and artificial intelligence explorations, proof-of-concepts, research, tools proof-of-technology and pilot projects. This is a fast paced highly visible and impactful group that has delivered more than 150 AI/ML/NLP innovation use cases since 2017.

In this role, you will:
Help/chaperone/shepherd AI/ML/NLP POCs, explorations, research projects in AA BLADE/Lab.
Carry out end-to-end functional, technology, security, and performance evaluations and testing of Big Data data-preparation tools, advanced analytics, BI and AI/ML tools and apps.
Take ownership of complex proof of technologies (POTs) and proof of concepts (POCs).
Be able to work with various vendors, startup companies, corporate supply chain, enterprise and data architects, tech teams, as well as data engineers, data scientist, and business partners and project managers.
Collaborate with Big Data platform (Hortonworks) tech leads, cloud (Google Cloud Platform) infrastructure engineers, and vendor resources.
Chaperone technically complex fast-paced POCs and POTs projects and programs to success.
Carry out hands-on development, configuration, data engineering, data preparation, data movement, and related tasks for POC/Pilot projects in Big Data environment.
Lead in adopting leading edge advanced analytics, ML, AI tools, Big-Data data preparation, and related tools for Enterprise Advanced Analytics Lab/BLADE.
Contribute to cloud migration strategy for data engineering and ML Ops solutions. Migrate ML Ops infrastructure from on-prem to private and public cloud (GCP)
Keep up with emerging best practices in ML-Ops and drive adoption as necessary.
Responsible for creating, and owning documents including User Manuals, Cookbooks, FAQ, and Wiki.
Required Qualifications:
B.S/B.Tech/B.E. degree or higher in a quantitative field such as computer sciences, applied math, statistics, engineering
10+ years of hands-on experience in data, advanced analytics architecture and design.
10+ years of solution architecture, analytics app dev, and data preparation and data engineering experience. Familiarity with databases, Teradata, data-lake, and cloud data-warehouse.
3 years of data science, AI/ML/NLP experience and expertise with Python, Spark, PySpark, etc.
At least 5 years of experience of Hadoop/Big Data development experience in Hortonworks, Cloudera, cloud computer and cloud analytics (in Google Cloud Platform using AIML Platform), Databricks, etc.
At least 5 years of experience in evaluating innovative advanced analytics, and data preparation tools.
3 years in MLOps/DevOps/DataOps.
10 years of Unix development, UNIX scripting, Java, Python, Scala experience.
10 years of data preparation wrangling, ETL, and data enrichment experience.
Deep understanding of Hadoop ecosystem, SAS, and related open source products.
Experience in analytics, in open source tools, libraries for R, Python, Spark, H2O, and others.
Familiarity with predictive analytics, real-time analytics, graph databases/analytics, cognitive computing, deep learning, cloud analytics, and geo spatial analytics.
Understanding of financial services, banking, and investment.
Ability to multi-task and work in an unstructured and interrupt driven environment.
Excellent communication skills and project management skills.
Ability to interact with both business and technology partners on tech migration/adoption
Dedicated, enthusiastic, driven and performance-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)
Data engineering experience across SQL databases like Teradata, Oracle and NoSQL databases like MongoDB, Cassandra
Experience in big data stack like Hadoop, Hive, Kafka, Spark
Experience with elastic search, knowledge graph
Experience with ML model testing: model performance, model health, etc.
Job Expectations:
As mentioned under responsibilities
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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By Richard