Data Scientist (Data & AI Engineer)

Department Icon Data Science Analytics & Machine Learning
Posted: 1 year ago
2-4 years
Bengaluru East, Karnataka, India
Data Science Analytics & Machine Learning
Work from Office
Full Time

Posted: 1 year ago
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Job Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.


The Client Services BI & Analytics team strives to create an open, trusting data culture where the cost of curiosity – the number of steps, amount of time, and complexity of effort needed to use operational data to derive insights – is as low as possible. We govern Client Services’ operational data and metrics, create easily usable dashboards and data sources, and analyze data to share insights.

We are a part of the Client Services Global Business Operations function and work with all levels of stakeholders, from executive leaders sharing insights with the C-Suite to customer-facing colleagues who rely on our assets to incorporate data into their daily responsibilities.

This specialist role makes data available from new sources, builds robust data models, creates and optimizes data enrichment pipelines, and provides engineering support to specific projects. You will partner with our Data Visualizers and Solution Designers to ensure that data needed by the business is available and accurate and to develop certified data sets. This technical lead and architect role is a force multiplier to our Visualizers, Analysts, and other data users across Client Services.

Responsibilities

  • Design, develop, and maintain scalable data pipelines and systems.

  • Monitor and troubleshoot data pipeline issues to ensure seamless data flow.

  • Establish data processes and automation based on business and technology requirements, leveraging Visa’s supported data platforms and tools

  • Deliver small to large data engineering and Machine learning projects either individually or as part of a project team

  • Setup ML Ops pipelines to Productionalize ML models and setting up Gen AI pipelines

  • Collaborate with cross-functional teams to understand data requirements and ensure data quality, with a focus on implementing data validation and data quality checks at various stages of the pipeline

  • Provide expertise in data warehousing, ETL, and data modeling to support data-driven decision making, with a strong understanding of best practices in data pipeline design and performance optimization

  • Extract and manipulate large datasets using standard tools such as Hadoop (Hive), Spark, Python (pandas, NumPy), Presto, and SQL

  • Develop data solutions using Agile principles

  • Provide ongoing production support

  • Communicate complex concepts in a clear and effective manner

  • Stay up to date with the latest data engineering trends and technologies to ensure the companys data infrastructure is always state-of-the-art, with an understanding of best practices in cloud-based data engineering

This is a remote position. A remote position does not require job duties be performed within proximity of a Visa office location. Remote positions may be required to be present at a Visa office with scheduled notice.

Qualifications

Basic Qualifications 

  • 2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)

Preferred Qualifications 

  • 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
  • 3+ years of work experience with a bachelor’s degree in the STEM field. 
  • Strong experience with SQL, Python, Hadoop, Spark, Hive, Airflow and MPP data bases
  • 5+ years of analytics experience with a focus on data Engineering and AI
  • Experience with both traditional data warehousing tools and techniques (such as SSIS, ODI, and on-prem SQL Server, Oracle) as well as modern technologies (such as Hadoop, Denodo, Spark, Airflow, and Python), and a solid understanding of best practices in data engineering 
  • Advanced knowledge of SQL (e.g., understands subqueries, self-joining tables, stored procedures, can read an execution plan, SQL tuning, etc.) 
  • Solid understanding of best practices in data warehousing, ETL, data modeling, and data architecture. 
  • Experience with NoSQL databases (e.g., MongoDB, Cassandra)
  • Experience with cloud-based data warehousing and data pipeline management (AWS, GCP, Azure) 
  • Experience in Python, Spark, and exposure to scheduling tools like Tuber/Airflow is preferred. 
  • Able to create data dictionaries, setup and monitor data validation alerts, and execute periodic jobs to maintain data pipelines for completed projects 
  • Experience with visualization software (e.g., Tableau, QlikView, PowerBI) is a plus. 
  • A team player and collaborator, able to work well with a diverse group of individuals in a matrixed environment 
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.

Skills

Data ValidationPythonData ArchitectureData ModelingData WarehousingEtlMachine LearningQlikviewVisualizationAnalyticsMl OpsAiMlSqlData ScientistAi Engineer

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About Company

Visa is a global payments technology company that connects consumers, businesses, financial institutions, and governments worldwide through its payment network.

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