Staff ML Scientist
Staff ML Scientist
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Job Description
Team Summary:
The Risk and Identity Solutions (RaIS) team provides risk management services for banks merchants and other payment networks. Machine learning and AI models are the heart of the realtime insights used by our clients to manage risk. Created by the Visa Predictive Models (VPM) team continual improvement and efficient deployment of these models is essential for our future success. To support our rapidly growing suite of predictive models we are looking for engineers who are passionate about managing large volumes of data creating efficient automated processes and standardizing ML/AI tools.
This is a great opportunity to work with a new Data Engineering and MLOps team to scale and structure large scale data engineering and ML/AI that drives significant revenue for Visa. As a member of the Risk and Identify Solutions modeling organization (VPM) your role will involve developing and implementing practices that will allow deployment of machine learning models in large data science projects.
You must be a handson expert able to navigate both data engineering and data science disciplines to build effective engineering solutions that support ML/AI models. You will partner closely with global stakeholders in RaIS Product VPM Data Science and Visa Research to help create and prioritize our strategic roadmap. You will then leverage your expert technical knowledge of data engineering tools and data architecture in the design and creation of the solutions on our roadmap.
The position is based at Visas offices in Bangalore India.
Essential Functions:
- Proficient in exploratory data analysis (EDA) using Pythons scientific libraries including numpy pandas matplotlib seaborn and scikitlearn
- Exposure to model development frameworks like MLFlow
- Experience using Papermill for parameterizing and executing Jupyter Notebooks
- Strong development experience in at least one of the following: Python R (preferably Python)
- Implementation of MLOps practices including continuous integration and deployment (CI/CD) for ML models
- Hands on experience in building and maintaining data pipelines feature engineering pipelines and comfortable with core ML concepts.
- Handson experience in engineering testing validating and productizing ML models for highperformance use cases
- Handson experience with AWS Sagemaker for building training and deploying ML models
- Develop and implement practices for deploying machine learning models in large data science projects
- Proven experience in building and training complex ML models
- Experience using and maintaining DevOps tools and implementing automations for production
- Additional knowledge of AWS services and ecosystems
- Experience working with containerized and virtualized environments (Docker K8s)
This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager.
Qualifications :
6 yrs. work experience with a Bachelors Degree or 5 years of work experience with a Masters or Advanced Degree in an analytical field such as computer science statistics finance economics or relevant area.
Technical skills:
- Proficient in exploratory data analysis (EDA) using Pythons scientific libraries including numpy pandas matplotlib seaborn and scikitlearn
- Exposure to frameworks like MLflow for model lifecycle management
- Strong development experience in programming languages preferably Python
- Implementation of MLOps practices including continuous integration and deployment (CI/CD) for ML models.
- Experience with complex highvolume multidimensional data as well as machine learning models based on unstructured structured and streaming datasets.
- Experience with Unix/Shell or Python scripting and exposure to scheduling tools like Oozie and Airflow.
- Handson experience with AWS SageMaker for building training and deploying ML models.
- Proven experience in building and training complex ML models.
- Experience using Papermill for parameterizing and executing Jupyter Notebooks.
- Experience with SQL for extracting aggregating and processing big data pipelines using Hadoop EMR and NoSQL Databases.
Additional Skills (Plus):
- Exposure to model serving engines such as Tensorflow Triton etc.
- Spark Pipelines: Build and maintain efficient and robust Spark pipelines to create and access data sets and feature stores for ML models.
- ETL processes: The role also involves developing and executing large scale ETL processes to support data quality reporting data marts and predictive modeling.
- Knowledge of standard Big data and Real Time stack such as Hadoop Spark Kafka Redis Flink and similar technologies
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
