Sr Data Scientist - ML Ops
Sr Data Scientist - ML Ops
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Job Description
To ensure that Visas payment technology is truly available to everyone everywhere requires the success of our key bank or merchant partners and internal business units. The Global Data Science group supports these partners by using our extraordinarily rich data set that spans more than 3 billion cards globally and captures more than 100 billion transactions in a single year. Our focus lies on building creative solutions that have an immediate impact on the business of our highly analytical partners. We work in complementary teams comprising members from Data Science and various groups at Visa. To support our rapidly growing group we are looking for ML Engineers focused on generating value for the payments ecosystem. We are dreaming of the next generation of AI features and products.
Responsible for building endtoend automated pipelines for AI/ML models including model training model validation model refit model recalibration model monitoring model serving etc.
Work collaboratively with Data Scientists Data Engineers and crossfunctional partners to design and deploy AI/ML based solutions and products
Lead end toend deployment and maintenance of machine learning models in production from concept design implementation to rollout ensuring the highest quality and performance
Mentor team members share knowledge and contribute to the technical growth of the team. Provide guidance on machine learning best practices and methodologies.
Conduct A/B tests and experiments to iterate and finetune algorithms and models.
Stay updated on stateoftheart algorithmic techniques and recognize promising innovations adapting them to Visas unique business and offerings.
Design implement and maintain reliable highperformance distributed systems.
Support Strategic planning business analysis and technical knowledge of ML Engineering tools and data architecture solutions.
Strong problemsolving capabilities and ability to quickly propose feasible solutions and effectively communicate strategy and risk mitigation approaches to leadership.
Essential Functions
Build AI/ML pipelines to support model development model production model validation model performance monitoring model recalibration continuous integration continuous delivery of AI/ML models.
New model development and existing model retraining performance evaluation and score optimization. Preferable to have data science knowledge and experience in designing developing and implementing Deep Learning methodologies and newer ML model implementations at scale.
Build and maintain high performing ETL processes including data quality and testing aligned across technology internal reporting and other functional teams.
Build ETL pipelines in Spark Python HIVE or Scala Airflow that process transaction and account level data and standardize data fields across various data sources
Exposure to model management and governance practices. Ability to take decisions around model drift to monitor and refine models continuously.
Create data dictionaries setup/monitor data validation alerts and execute periodic jobs like performance dashboards predictive models scoring for clients deliverables
Define and build technical/data documentation and experience with code version control systems (for e.g. git). Ensure data accuracy integrity and consistency
This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 23 set days a week (determined by leadership/site) with a general guidepost of being in the office 50% or more of the time based on business needs.
Qualifications :
Basic Qualifications
4 years of work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters MBA JD MD) or 0 years of work experience with a PhD degree
Preferred Qualifications
68 years of work experience with a Bachelors Degree or 46 years of work experience with an Advanced Degree (e.g. Masters MBA JD MD) or 3 years of experience with a PhD
4 years experience in databased decisionmaking or quantitative analysis
Masters degree in Statistics Operations Research Applied Mathematics Economics Data Science Business Analytics Computer Science or a related technical field
Extracting and aggregating data from large data sets using SQL/Hive or Spark
Analyzing large data sets using programming languages such as Python R SQL and/or Spark
Generating and visualizing databased insights in software such as Tableau
Advanced knowledge and experience of AI/ML model development and implementation
Experienced with building AI/ML model pipelines and creating robust and scalable AI/ML solutions.
Track record of creating robust and scalable AI/ML/Data Science solutions and products
Technical Skills:
Working knowledge of Hadoop ecosystem and associated technologies (For e.g. Apache Spark MLlib GraphX iPython scikit Pandas etc.)
Advanced programming ability in different programming languages such as Spark Python SQL Scala.
Experience working with Airflow Github ML flow for building and maintain ETL pipeline.
Proficient in advanced data mining and statistical modeling techniques including Predictive modeling (e.g. binomial and multinomial regression ANOVA) Classification techniques (e.g. Clustering Principal Component Analysis factor analysis) Decision Tree techniques (e.g. CART CHAID).
Expert knowledge in Deep Learning techniques and LLM.
Experience working with large scale data ingestion processing and storage in distributed computing environments / big data platforms (Hadoop) as well as common database systems and value stores (Parquet Avro HBase etc.).
Familiarity with both common computing environments (e.g. Linux Shell Scripting) and commonly used IDEs (Jupyter Notebooks).
Experience working in building and integrating the code in the defined CI/CD framework using git.
Experience working with AWS for MLOps model development and model implementation is preferred but not required.
Preferred experience with Visualization Tools like Tableau Power BI and D3
Additional Information :
Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race color religion sex national origin sexual orientation gender identity disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
