ML Ops and Data Engineering Manager Job Vacancy in Wells Fargo Bengaluru, Karnataka – Updated today

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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 Leader to join our team and help us solve challenging and interesting business problems through end-to-end ownership of data pipelines, feature stores, ML workflows, deployment, monitoring and model service. This leadership role will play a key role in setting up and scaling ML Ops and Engineering functions and culture within the organization. Incumbent is expected to manage highly matrixed organizations, with additional responsibility to drive ML Ops best practices in collaboration with Data Science and platforms teams.

In this role, you will:
Supporting NLP, ML and AI operational teams with the advanced know-how blending theory and practice
Providing technical consulting to business leaders at an appropriate level of information encapsulation
Create scalable and modularized data engineering solutions to standardize and automate process of data ingestion and pipeline creation, from multiple data sources (for both structured an unstructured data)
Ingest and integrate data from SQL and NoSQL data sources, data lakes, free text, etc. with proper adherence to lineage and quality best practices
Enable fast and scaled feature engineering for various data science use cases. Build feature store and apply version control and governance ensuring single source of truth
Oversee development and scaling of end-to-end ML Ops team and capability. Work with data science and technology leaders and chalk out the ML Ops roadmap and implementation strategy
Lead post deployment model monitoring capabilities and integrate feedback from monitoring into training pipeline
Develop a suite of model serving capabilities including MLaaS (Machine Learning as-a-service), supporting on-prem and cloud deployments
Lead cloud migration strategy for data engineering and ML Ops solutions
Apply critical thinking skills, along with technological and AI/ML knowhow to solve complex and multi-faceted business problems.
Be a talent magnet by collaborating with various universities and leveraging network across companies
Coaching team members to operate at higher level of dimensionality to innovate and bring in game changing ideas to fruition
Demonstrated ability to speak at internal and external conferences
Work closely with innovation group, think tanks within WF and across the industry
Proven experience in the area of innovation evidenced by successful holding of one or more patents
Work closely with business partners, data stewards, project/program managers, and other IT teams to turn data into critical information and knowledge that can be used to make sound organizational decisions.
Liaison with other COEs at the bank, interface with centralized model governance group to effectively create and manage an ecosystem of ML Ops
As a team member and manager, you are expected to achieve success by leading yourself, your team and the business. Specifically, you will lead your team with integrity and create an environment where your team members feel included, valued and supported to do work that energizes them. Management responsibilities will also include providing ongoing coaching and feedback, recognizing and developing team members, identifying and managing risks and completing daily management tasks.

Required Qualifications:
12 plus years in relevant field (across ML Ops, data engineering, analytics, BI, data management/warehousing, DevOps)
PhD or Masters degree in operations research, applied mathematics, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis.
~10 years advanced programming exposure in Python, SQL, Scala, Java, SAS
~10 years of experience across SQL databases like Teradata, Oracle and NoSQL databases like MongoDB, Cassandra
~5 years of experience in big data stack like Hadoop, Hive, Kafka, Spark
~4 years of experience in ML workflow technology like Airflow, Kubeflow
~3 years of experience in deployment through containers (like Docker) and orchestration (Kubernetes)
~3 years of experience in deploying Machine Learning as-a-service using REST API’s, Flask, Django, etc.
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 creating data pipelines and ML Ops environment on Cloud (GCP, AWS, Azure) (preferred)
Experience in banking and BFSI, retail, e-commerce, product companies (preferred)
4+ years of good team handling experience of managing people and projects
Able to guide, mentor and provide technical assistance to the team
Ensures adherence to data management/data governance regulations and policies. Data involved may be very large, structured or unstructured, and from multiple sources.
Persuasive written and verbal communication skills, writing white papers is a plus
Prior experience of attending prestigious conferences as an attendee or as panelist or speaker is weighed heavily
Proven experience in the area of innovation evidenced by successful holding of one or more patents
Visiting faculty or expert professionals, with the ability to see through the product roadmap for 2 or more years may have an edge in the interview process
Desired Qualifications:
Good to have certifications in Data Science, Data Engineering, ML Ops, Cloud services
Ability to prioritize work, meet deadlines, achieve goals and work under pressure in a dynamic and complex environment
Detail oriented, results driven, and has the ability to navigate in a quickly changing and high demand environment while balancing multiple priorities
Ability to research and report on a variety of issues using problem solving skills
Ability to interact with integrity and a high level of professionalism with all levels of team members and management
Ability to make timely and independent judgment decisions while working in a fast-paced and results-driven environment
Ability to learn the business aspects quickly, multitask and prioritize between projects.
Exhibits appropriate sense of urgency in managing responsibilities
Ability to accurately process high volumes of work within established deadlines
Available to flex schedule periodically per business requirements
Demonstrate strong negotiation, communication & presentation skills
Demonstrates a high degree of reliability, integrity and trustworthiness
Takes ownership for responsibilities for own and drive same effort to the team
Dedicated, enthusiastic, driven and performance-oriented; possesses a strong work ethic and good team player
Be proactive and get engaged in organizational initiatives
Job Expectations:
Build and drive ML Ops and DE practices, team and solutions
Lead the organization through change management over cloud adoption
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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